Analysis of Zinc-Exporters Expression in Prostate Cancer.

PubMed

Singh, Chandra K; Malas, Kareem M; Tydrick, Caitlin; Siddiqui, Imtiaz A; Iczkowski, Kenneth A; Ahmad, Nihal

2016-11-11

Maintaining optimal intracellular zinc (Zn) concentration is crucial for critical cellular functions. Depleted Zn has been associated with prostate cancer (PCa) progression. Solute carrier family 30 (SLC30A) proteins maintain cytoplasmic Zn balance by exporting Zn out to the extracellular space or by sequestering cytoplasmic Zn into intracellular compartments. In this study, we determined the involvement of Zn-exporters, SLC30A 1-10 in PCa, in the context of racial health disparity in human PCa samples obtained from European-American (EA) and African-American (AA) populations. We also analyzed the levels of Zn-exporters in a panel of PCa cells derived from EA and AA populations. We further explored the expression profile of Zn-exporters in PCa using Oncomine database. Zn-exporters were found to be differentially expressed at the mRNA level, with a significant upregulation of SLC30A1, SLC30A9 and SLC30A10, and downregulation of SLC30A5 and SLC30A6 in PCa, compared to benign prostate. Moreover, Ingenuity Pathway analysis revealed several interactions of Zn-exporters with certain tumor suppressor and promoter proteins known to be modulated in PCa. Our study provides an insight regarding Zn-exporters in PCa, which may open new avenues for future studies aimed at enhancing the levels of Zn by modulating Zn-transporters via pharmacological means.

Analysis of Zinc-Exporters Expression in Prostate Cancer

PubMed Central

Singh, Chandra K.; Malas, Kareem M.; Tydrick, Caitlin; Siddiqui, Imtiaz A.; Iczkowski, Kenneth A.; Ahmad, Nihal

2016-01-01

Maintaining optimal intracellular zinc (Zn) concentration is crucial for critical cellular functions. Depleted Zn has been associated with prostate cancer (PCa) progression. Solute carrier family 30 (SLC30A) proteins maintain cytoplasmic Zn balance by exporting Zn out to the extracellular space or by sequestering cytoplasmic Zn into intracellular compartments. In this study, we determined the involvement of Zn-exporters, SLC30A 1–10 in PCa, in the context of racial health disparity in human PCa samples obtained from European-American (EA) and African-American (AA) populations. We also analyzed the levels of Zn-exporters in a panel of PCa cells derived from EA and AA populations. We further explored the expression profile of Zn-exporters in PCa using Oncomine database. Zn-exporters were found to be differentially expressed at the mRNA level, with a significant upregulation of SLC30A1, SLC30A9 and SLC30A10, and downregulation of SLC30A5 and SLC30A6 in PCa, compared to benign prostate. Moreover, Ingenuity Pathway analysis revealed several interactions of Zn-exporters with certain tumor suppressor and promoter proteins known to be modulated in PCa. Our study provides an insight regarding Zn-exporters in PCa, which may open new avenues for future studies aimed at enhancing the levels of Zn by modulating Zn-transporters via pharmacological means. PMID:27833104

Revealing the ultrafast outflow in IRAS 13224-3809 through spectral variability

NASA Astrophysics Data System (ADS)

Parker, M. L.; Alston, W. N.; Buisson, D. J. K.; Fabian, A. C.; Jiang, J.; Kara, E.; Lohfink, A.; Pinto, C.; Reynolds, C. S.

2017-08-01

We present an analysis of the long-term X-ray variability of the extreme narrow-line Seyfert 1 galaxy IRAS 13224-3809 using principal component analysis (PCA) and fractional excess variability (Fvar) spectra to identify model-independent spectral components. We identify a series of variability peaks in both the first PCA component and Fvar spectrum which correspond to the strongest predicted absorption lines from the ultrafast outflow (UFO) discovered by Parker et al. (2017). We also find higher order PCA components, which correspond to variability of the soft excess and reflection features. The subtle differences between RMS and PCA results argue that the observed flux-dependence of the absorption is due to increased ionization of the gas, rather than changes in column density or covering fraction. This result demonstrates that we can detect outflows from variability alone and that variability studies of UFOs are an extremely promising avenue for future research.

Prostate Cancer Associated Lipid Signatures in Serum Studied by ESI-Tandem Mass Spectrometryas Potential New Biomarkers.

PubMed

Duscharla, Divya; Bhumireddy, Sudarshana Reddy; Lakshetti, Sridhar; Pospisil, Heike; Murthy, P V L N; Walther, Reinhard; Sripadi, Prabhakar; Ummanni, Ramesh

2016-01-01

Prostate cancer (PCa) is one amongst the most common cancersin western men. Incidence rate ofPCa is on the rise worldwide. The present study deals with theserum lipidome profiling of patients diagnosed with PCa to identify potential new biomarkers. We employed ESI-MS/MS and GC-MS for identification of significantly altered lipids in cancer patient's serum compared to controls. Lipidomic data revealed 24 lipids are significantly altered in cancer patinet's serum (n = 18) compared to normal (n = 18) with no history of PCa. By using hierarchical clustering and principal component analysis (PCA) we could clearly separate cancer patients from control group. Correlation and partition analysis along with Formal Concept Analysis (FCA) have identified that PC (39:6) and FA (22:3) could classify samples with higher certainty. Both the lipids, PC (39:6) and FA (22:3) could influence the cataloging of patients with 100% sensitivity (all 18 control samples are classified correctly) and 77.7% specificity (of 18 tumor samples 4 samples are misclassified) with p-value of 1.612×10-6 in Fischer's exact test. Further, we performed GC-MS to denote fatty acids altered in PCa patients and found that alpha-linolenic acid (ALA) levels are altered in PCa. We also performed an in vitro proliferation assay to determine the effect of ALA in survival of classical human PCa cell lines LNCaP and PC3. We hereby report that the altered lipids PC (39:6) and FA (22:3) offer a new set of biomarkers in addition to the existing diagnostic tests that could significantly improve sensitivity and specificity in PCa diagnosis.

Prostate Cancer Associated Lipid Signatures in Serum Studied by ESI-Tandem Mass Spectrometryas Potential New Biomarkers

PubMed Central

Duscharla, Divya; Bhumireddy, Sudarshana Reddy; Lakshetti, Sridhar; Pospisil, Heike; Murthy, P. V. L. N.; Walther, Reinhard; Sripadi, Prabhakar; Ummanni, Ramesh

2016-01-01

Prostate cancer (PCa) is one amongst the most common cancersin western men. Incidence rate ofPCa is on the rise worldwide. The present study deals with theserum lipidome profiling of patients diagnosed with PCa to identify potential new biomarkers. We employed ESI-MS/MS and GC-MS for identification of significantly altered lipids in cancer patient’s serum compared to controls. Lipidomic data revealed 24 lipids are significantly altered in cancer patinet’s serum (n = 18) compared to normal (n = 18) with no history of PCa. By using hierarchical clustering and principal component analysis (PCA) we could clearly separate cancer patients from control group. Correlation and partition analysis along with Formal Concept Analysis (FCA) have identified that PC (39:6) and FA (22:3) could classify samples with higher certainty. Both the lipids, PC (39:6) and FA (22:3) could influence the cataloging of patients with 100% sensitivity (all 18 control samples are classified correctly) and 77.7% specificity (of 18 tumor samples 4 samples are misclassified) with p-value of 1.612×10−6 in Fischer’s exact test. Further, we performed GC-MS to denote fatty acids altered in PCa patients and found that alpha-linolenic acid (ALA) levels are altered in PCa. We also performed an in vitro proliferation assay to determine the effect of ALA in survival of classical human PCa cell lines LNCaP and PC3. We hereby report that the altered lipids PC (39:6) and FA (22:3) offer a new set of biomarkers in addition to the existing diagnostic tests that could significantly improve sensitivity and specificity in PCa diagnosis. PMID:26958841

Epigenetics-related genes in prostate cancer: expression profile in prostate cancer tissues, androgen-sensitive and -insensitive cell lines.

PubMed

Shaikhibrahim, Zaki; Lindstrot, Andreas; Ochsenfahrt, Jacqueline; Fuchs, Kerstin; Wernert, Nicolas

2013-01-01

Epigenetic changes have been suggested to drive prostate cancer (PCa) development and progression. Therefore, in this study, we aimed to identify novel epigenetics-related genes in PCa tissues, and to examine their expression in metastatic PCa cell lines. We analyzed the expression of epigenetics-related genes via a clustering analysis based on gene function in moderately and poorly differentiated PCa glands compared to normal glands of the peripheral zone (prostate proper) from PCa patients using Whole Human Genome Oligo Microarrays. Our analysis identified 12 epigenetics-related genes with a more than 2-fold increase or decrease in expression and a p-value <0.01. In modera-tely differentiated tumors compared to normal glands of the peripheral zone, we found the genes, TDRD1, IGF2, DICER1, ADARB1, HILS1, GLMN and TRIM27, to be upregulated, whereas TNRC6A and DGCR8 were found to be downregulated. In poorly differentiated tumors, we found TDRD1, ADARB and RBM3 to be upregulated, whereas DGCR8, PIWIL2 and BC069781 were downregulated. Our analysis of the expression level for each gene in the metastatic androgen-sensitive VCaP and LNCaP, and -insensitive PC3 and DU-145 PCa cell lines revealed differences in expression among the cell lines which may reflect the different biological properties of each cell line, and the potential role of each gene at different metastatic sites. The novel epigenetics-related genes that we identified in primary PCa tissues may provide further insight into the role that epigenetic changes play in PCa. Moreover, some of the genes that we identified may play important roles in primary PCa and metastasis, in primary PCa only, or in metastasis only. Follow-up studies are required to investigate the functional role and the role that the expression of these genes play in the outcome and progression of PCa using tissue microarrays.

Multivariate analysis of historical data (2004-2013) in assessing the possible environmental impact of the Bellolampo landfill (Palermo).

PubMed

Indelicato, Serena; Bongiorno, David; Tuzzolino, Nicola; Mannino, Maria Rosaria; Muscarella, Rosalia; Fradella, Pasquale; Gargano, Maria Elena; Nicosia, Salvatore; Ceraulo, Leopoldo

2018-03-14

Multivariate analysis was performed on a large data set of groundwater and leachate samples collected during 9 years of operation of the Bellolampo municipal solid waste landfill (located above Palermo, Italy). The aim was to obtain the most likely correlations among the data. The analysis results are presented. Groundwater samples were collected in the period 2004-2013, whereas the leachate analysis refers to the period 2006-2013. For groundwater, statistical data evaluation revealed notable differences among the samples taken from the numerous wells located around the landfill. Characteristic parameters revealed by principal component analysis (PCA) were more deeply investigated, and corresponding thematic maps were drawn. The composition of the leachate was also thoroughly investigated. Several chemical macro-descriptors were calculated, and the results are presented. A comparison of PCA results for the leachate and groundwater data clearly reveals that the groundwater's main components substantially differ from those of the leachate. This outcome strongly suggests excluding leachate permeation through the multiple landfill lining.

Circular RNA Myosin Light Chain Kinase (MYLK) Promotes Prostate Cancer Progression through Modulating Mir-29a Expression.

PubMed

Dai, Yuanqing; Li, Dongjie; Chen, Xiong; Tan, Xinji; Gu, Jie; Chen, Mingquan; Zhang, Xiaobo

2018-05-25

BACKGROUND In developed countries, prostate cancer (PCa) is a frequently diagnosed cancer with the second highest fatality rate. Circular RNAs (circRNAs) are a class of endogenous non-coding RNAs (ncRNAs) stably expressed in cells and involved in a series of carcinomas. However, few research studies have reported on the role of circRNAs in PCa. MATERIAL AND METHODS We used qRT-PCR to detect the expression of circMYLK (circRNA ID: hsa_circ_0141940) and miR-29a in PCa tissues and cell lines. MTT, colony formation, and TUNEL assays were performed to analysis the cell viability of PCa cells. Transwell and wound scratch assays were performed to investigate the cell invasion and migration of PCa cells. RESULTS In the present study, we confirmed that circMYLK expression level was significantly higher in PCa samples and PCa cells than in normal tissues and normal prostatic cells. The upregulated circRNA-MYLK promoted PCa cells proliferation, invasion, and migration; however, si-circRNA-MYLK significantly accelerated the PCa cell apoptosis. We also observed that the aforementioned function of circRNA-MYLK on PCa cells was affected through targeting miR-29a. CONCLUSIONS We confirmed circRNA-MYLK was an oncogene in PCa and revealed a novel mechanism underlying circRNA-MYLK in PC progression.

Investigation of cell wall composition related to stem lodging resistance in wheat (Triticum aestivum L.) by FTIR spectroscopy.

PubMed

Wang, Jian; Zhu, Jinmao; Huang, RuZhu; Yang, YuSheng

2012-07-01

We explored the rapid qualitative analysis of wheat cultivars with good lodging resistances by Fourier transform infrared resonance (FTIR) spectroscopy and multivariate statistical analysis. FTIR imaging showing that wheat stem cell walls were mainly composed of cellulose, pectin, protein, and lignin. Principal components analysis (PCA) was used to eliminate multicollinearity among multiple peak absorptions. PCA revealed the developmental internodes of wheat stems could be distributed from low to high along the load of the second principal component, which was consistent with the corresponding bands of cellulose in the FTIR spectra of the cell walls. Furthermore, four distinct stem populations could also be identified by spectral features related to their corresponding mechanical properties via PCA and cluster analysis. Histochemical staining of four types of wheat stems with various abilities to resist lodging revealed that cellulose contributed more than lignin to the ability to resist lodging. These results strongly suggested that the main cell wall component responsible for these differences was cellulose. Therefore, the combination of multivariate analysis and FTIR could rapidly screen wheat cultivars with good lodging resistance. Furthermore, the application of these methods to a much wider range of cultivars of unknown mechanical properties promises to be of interest.

Comparison of common components analysis with principal components analysis and independent components analysis: Application to SPME-GC-MS volatolomic signatures.

PubMed

Bouhlel, Jihéne; Jouan-Rimbaud Bouveresse, Delphine; Abouelkaram, Said; Baéza, Elisabeth; Jondreville, Catherine; Travel, Angélique; Ratel, Jérémy; Engel, Erwan; Rutledge, Douglas N

2018-02-01

The aim of this work is to compare a novel exploratory chemometrics method, Common Components Analysis (CCA), with Principal Components Analysis (PCA) and Independent Components Analysis (ICA). CCA consists in adapting the multi-block statistical method known as Common Components and Specific Weights Analysis (CCSWA or ComDim) by applying it to a single data matrix, with one variable per block. As an application, the three methods were applied to SPME-GC-MS volatolomic signatures of livers in an attempt to reveal volatile organic compounds (VOCs) markers of chicken exposure to different types of micropollutants. An application of CCA to the initial SPME-GC-MS data revealed a drift in the sample Scores along CC2, as a function of injection order, probably resulting from time-related evolution in the instrument. This drift was eliminated by orthogonalization of the data set with respect to CC2, and the resulting data are used as the orthogonalized data input into each of the three methods. Since the first step in CCA is to norm-scale all the variables, preliminary data scaling has no effect on the results, so that CCA was applied only to orthogonalized SPME-GC-MS data, while, PCA and ICA were applied to the "orthogonalized", "orthogonalized and Pareto-scaled", and "orthogonalized and autoscaled" data. The comparison showed that PCA results were highly dependent on the scaling of variables, contrary to ICA where the data scaling did not have a strong influence. Nevertheless, for both PCA and ICA the clearest separations of exposed groups were obtained after autoscaling of variables. The main part of this work was to compare the CCA results using the orthogonalized data with those obtained with PCA and ICA applied to orthogonalized and autoscaled variables. The clearest separations of exposed chicken groups were obtained by CCA. CCA Loadings also clearly identified the variables contributing most to the Common Components giving separations. The PCA Loadings did not highlight the most influencing variables for each separation, whereas the ICA Loadings highlighted the same variables as did CCA. This study shows the potential of CCA for the extraction of pertinent information from a data matrix, using a procedure based on an original optimisation criterion, to produce results that are complementary, and in some cases may be superior, to those of PCA and ICA. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of Surface Water Quality along the Coast of Sanya, South China Sea

PubMed Central

Wu, Zhen-Zhen; Che, Zhi-Wei; Wang, You-Shao; Dong, Jun-De; Wu, Mei-Lin

2015-01-01

Principal component analysis (PCA) and cluster analysis (CA) are utilized to identify the effects caused by human activities on water quality along the coast of Sanya, South China Sea. PCA and CA identify the seasonality of water quality (dry and wet seasons) and polluted status (polluted area). The seasonality of water quality is related to climate change and Southeast monsoons. Spatial pattern is mainly related to anthropogenic activities (especially land input of pollutions). PCA reveals the characteristics underlying the generation of coastal water quality. The temporal and spatial variation of the trophic status along the coast of Sanya is governed by hydrodynamics and human activities. The results provide a novel typological understanding of seasonal trophic status in a shallow, tropical, open marine bay. PMID:25894980

Qualitative analysis of precipitate formation on the surface and in the tubules of dentin irrigated with sodium hypochlorite and a final rinse of chlorhexidine or QMiX.

PubMed

Kolosowski, Kamil P; Sodhi, Rana N S; Kishen, Anil; Basrani, Bettina R

2014-12-01

Interaction of sodium hypochlorite (NaOCl) mixed with chlorhexidine (CHX) produces a brown precipitate containing para-chloroaniline (PCA). When QMiX is mixed with NaOCl, no precipitate forms, but color change occurs. The aim of this study was to qualitatively assess the formation of precipitate and PCA on the surface and in the tubules of dentin irrigated with NaOCl, followed either by EDTA, NaOCl, and CHX or by saline and QMiX by using time-of-flight secondary ion mass spectrometry (TOF-SIMS). Dentin blocks were obtained from human maxillary molars, embedded in resin, and cross-sectioned to expose dentin. Specimens in group 1 were immersed in 2.5% NaOCl, followed by 17% EDTA, 2.5% NaOCl, and 2% CHX. Specimens in group 2 were immersed in 2.5% NaOCl, followed by saline and QMiX. The dentin surfaces were subjected to TOF-SIMS spectra analysis. Longitudinal sections of dentin blocks were then exposed and subjected to TOF-SIMS analysis. All samples and analysis were performed in triplicate for confirmation. TOF-SIMS analysis of group 1 revealed an irregular precipitate, containing PCA and CHX breakdown products, on the dentin surfaces, occluding and extending into the tubules. In TOF-SIMS analysis of group 2, no precipitates, including PCA, were detected on the dentin surface or in the tubules. Within the limitations of this study, precipitate containing PCA was formed in the tubules of dentin irrigated with NaOCl followed by CHX. No precipitates or PCA were detected in the tubules of dentin irrigated with NaOCl followed by saline and QMiX. Copyright © 2014 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Meta-analysis of CDKN2A methylation to find its role in prostate cancer development and progression, and also to find the effect of CDKN2A expression on disease-free survival (PRISMA).

PubMed

Cao, Zipei; Wei, Lijuan; Zhu, Weizhi; Yao, Xuping

2018-03-01

Reduction of cyclin-dependent kinase inhibitor 2A (CDKN2A) (p16 and p14) expression through DNA methylation has been reported in prostate cancer (PCa). This meta-analysis was conducted to assess the difference of p16 and p14 methylation between PCa and different histological types of nonmalignant controls and the correlation of p16 or p14 methylation with clinicopathological features of PCa. According to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement criteria, articles were searched in PubMed, Embase, EBSCO, Wanfang, and CNKI databases. The strength of correlation was calculated by the pooled odds ratios (ORs) and their corresponding 95% confidence intervals (95% CIs). Trial sequential analysis (TSA) was used to estimate the required population information for significant results. A total of 20 studies published from 1997 to 2017 were identified in this meta-analysis, including 1140 PCa patients and 530 cases without cancer. Only p16 methylation in PCa was significantly higher than in benign prostatic lesions (OR = 4.72, P = .011), but had a similar level in PCa and adjacent tissues or high-grade prostatic intraepithelial neoplasias (HGPIN). TSA revealed that this analysis on p16 methylation is a false positive result in cancer versus benign prostatic lesions (the estimated required information size of 5116 participants). p16 methylation was not correlated with PCa in the urine and blood. Besides, p16 methylation was not linked to clinical stage, prostate-specific antigen (PSA) level, and Gleason score (GS) of patients with PCa. p14 methylation was not correlated with PCa in tissue and urine samples. No correlation was observed between p14 methylation and clinical stage or GS. CDKN2A mutation and copy number alteration were not associated with prognosis of PCa in overall survival and disease-free survival. CDKN2A expression was not correlated with the prognosis of PCa in overall survival (492 cases) (P > .1), while CDKN2A expression was significantly associated with a poor disease-free survival (P < .01). CDKN2A methylation may not be significantly associated with the development, progression of PCa. Although CDKN2A expression had an unfavorable prognosis in disease-free survival. More studies are needed to confirm our results.

Prostate Cancer Predictive Simulation Modelling, Assessing the Risk Technique (PCP-SMART): Introduction and Initial Clinical Efficacy Evaluation Data Presentation of a Simple Novel Mathematical Simulation Modelling Method, Devised to Predict the Outcome of Prostate Biopsy on an Individual Basis.

PubMed

Spyropoulos, Evangelos; Kotsiris, Dimitrios; Spyropoulos, Katherine; Panagopoulos, Aggelos; Galanakis, Ioannis; Mavrikos, Stamatios

2017-02-01

We developed a mathematical "prostate cancer (PCa) conditions simulating" predictive model (PCP-SMART), from which we derived a novel PCa predictor (prostate cancer risk determinator [PCRD] index) and a PCa risk equation. We used these to estimate the probability of finding PCa on prostate biopsy, on an individual basis. A total of 371 men who had undergone transrectal ultrasound-guided prostate biopsy were enrolled in the present study. Given that PCa risk relates to the total prostate-specific antigen (tPSA) level, age, prostate volume, free PSA (fPSA), fPSA/tPSA ratio, and PSA density and that tPSA ≥ 50 ng/mL has a 98.5% positive predictive value for a PCa diagnosis, we hypothesized that correlating 2 variables composed of 3 ratios (1, tPSA/age; 2, tPSA/prostate volume; and 3, fPSA/tPSA; 1 variable including the patient's tPSA and the other, a tPSA value of 50 ng/mL) could operate as a PCa conditions imitating/simulating model. Linear regression analysis was used to derive the coefficient of determination (R 2 ), termed the PCRD index. To estimate the PCRD index's predictive validity, we used the χ 2 test, multiple logistic regression analysis with PCa risk equation formation, calculation of test performance characteristics, and area under the receiver operating characteristic curve analysis using SPSS, version 22 (P < .05). The biopsy findings were positive for PCa in 167 patients (45.1%) and negative in 164 (44.2%). The PCRD index was positively signed in 89.82% positive PCa cases and negative in 91.46% negative PCa cases (χ 2 test; P < .001; relative risk, 8.98). The sensitivity was 89.8%, specificity was 91.5%, positive predictive value was 91.5%, negative predictive value was 89.8%, positive likelihood ratio was 10.5, negative likelihood ratio was 0.11, and accuracy was 90.6%. Multiple logistic regression revealed the PCRD index as an independent PCa predictor, and the formulated risk equation was 91% accurate in predicting the probability of finding PCa. On the receiver operating characteristic analysis, the PCRD index (area under the curve, 0.926) significantly (P < .001) outperformed other, established PCa predictors. The PCRD index effectively predicted the prostate biopsy outcome, correctly identifying 9 of 10 men who were eventually diagnosed with PCa and correctly ruling out PCa for 9 of 10 men who did not have PCa. Its predictive power significantly outperformed established PCa predictors, and the formulated risk equation accurately calculated the probability of finding cancer on biopsy, on an individual patient basis. Copyright © 2016 Elsevier Inc. All rights reserved.

Flight test of a propulsion controlled aircraft system on the NASA F-15 airplane

NASA Technical Reports Server (NTRS)

Burcham, Frank W., Jr.; Maine, Trindel A.

1995-01-01

Flight tests of the propulsion controlled aircraft (PCA) system on the NASA F-15 airplane evolved as a result of a long series of simulation and flight tests. Initially, the simulation results were very optimistic. Early flight tests showed that manual throttles-only control was much more difficult than the simulation, and a flight investigation was flown to acquire data to resolve this discrepancy. The PCA system designed and developed by MDA evolved as these discrepancies were found and resolved, requiring redesign of the PCA software and modification of the flight test plan. Small throttle step inputs were flown to provide data for analysis, simulation update, and control logic modification. The PCA flight tests quickly revealed less than desired performance, but the extensive flexibility built into the flight PCA software allowed rapid evaluation of alternate gains, filters, and control logic, and within 2 weeks, the PCA system was functioning well. The initial objective of achieving adequate control for up-and-away flying and approaches was satisfied, and the option to continue to actual landings was achieved. After the PCA landings were accomplished, other PCA features were added, and additional maneuvers beyond those originally planned were flown. The PCA system was used to recover from extreme upset conditions, descend, and make approaches to landing. A heading mode was added, and a single engine plus rudder PCA mode was also added and flown. The PCA flight envelope was expanded far beyond that originally designed for. Guest pilots from the USAF, USN, NASA, and the contractor also flew the PCA system and were favorably impressed.

Association of microRNA-21 expression with clinicopathological characteristics and the risk of progression in advanced prostate cancer patients receiving androgen deprivation therapy.

PubMed

Guan, Yangbo; Wu, You; Liu, Yifei; Ni, Jian; Nong, Shaojun

2016-08-01

Despite androgen deprivation therapy (ADT) remains the mainstay therapy for advanced prostate cancer (PCa), the patients have widely variable durations of response to ADT. Unfortunately, there is limited knowledge of pre-treatment prognostic factors for response to ADT. Recently, microRNA-21 (miR-21) has been reported to play an important role in development of castration resistance of CaP. However, little is known about the expression of miR-21 in advanced PCa biopsy tissues, and data on its potential predictive value in advanced PCa are completely lacking. In this study, paraffin-embedded prostate carcinoma tissues obtained by needle biopsy from 85 advanced PCa patients were evaluated for the expression levels of miR-21 by quantitative real-time PCR (qRT-PCR). In situ hybridization (ISH) analysis was performed to further confirm the qRT-PCR results. Kaplan-Meier analysis and Cox proportional hazards regression models were performed to investigate the correlation between miR-21 expression and time to progression of advanced PCa patients. Compared with adjacent non-cancerous prostate tissues, the expression level of miR-21 was significantly increased in PCa tissues (PCa vs. non-cancerous prostate: 1.3273 ± 0.3207 vs. 0.9970 ± 0.2054, P < 0.001). By and large, in ISH analysis miR-21 was expressed at a higher level in tumor areas than in adjacent non-cancerous areas. Additionally, PCa patients with higher expression of miR-21 were significantly more likely to be of high Gleason score and high clinical stage (P < 0.05). There was no significant association between miR-21 expression and the initial prostate-specific antigen (PSA) level or age at diagnosis. Moreover, Kaplan-Meier survival analysis found that PCa patients with high miR-21 expression have shorter progression-free survival than those with low miR-21 expression. Furthermore, Multivariate Cox analysis revealed both miR-21 expression status (P = 0.040) and clinical stage (P = 0.042) were all independent predictive factor for progression-free survival for advanced PCa. These findings suggest for the first time that the up-regulation of miR-21 may serve as an independent predictor of progress-free survival in patients with advanced PCa. Prostate 76:986-993, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Metabolic fingerprint of Brazilian maize landraces silk (stigma/styles) using NMR spectroscopy and chemometric methods.

PubMed

Kuhnen, Shirley; Bernardi Ogliari, Juliana; Dias, Paulo Fernando; da Silva Santos, Maiara; Ferreira, Antônio Gilberto; Bonham, Connie C; Wood, Karl Vernon; Maraschin, Marcelo

2010-02-24

Aqueous extract from maize silks is used by traditional medicine for the treatment of several ailments, mainly related to the urinary system. This work focuses on the application of NMR spectroscopy and chemometric analysis for the determination of metabolic fingerprint and pattern recognition of silk extracts from seven maize landraces cultivated in southern Brazil. Principal component analysis (PCA) of the (1)H NMR data set showed clear discrimination among the maize varieties by PC1 and PC2, pointing out three distinct metabolic profiles. Target compounds analysis showed significant differences (p < 0.05) in the contents of protocatechuic acid, gallic acid, t-cinnamic acid, and anthocyanins, corroborating the discrimination of the genotypes in this study as revealed by PCA analysis. Thus the combination of (1)H NMR and PCA is a useful tool for the discrimination of maize silks in respect to their chemical composition, including rapid authentication of the raw material of current pharmacological interest.

Analysis of antique bronze coins by Laser Induced Breakdown Spectroscopy and multivariate analysis

NASA Astrophysics Data System (ADS)

Bachler, M. Orlić; Bišćan, M.; Kregar, Z.; Jelovica Badovinac, I.; Dobrinić, J.; Milošević, S.

2016-09-01

This work presents a feasibility study of applying the Principal Component Analysis (PCA) to data obtained by Laser-Induced Breakdown Spectroscopy (LIBS) with the aim of determining correlation between different samples. The samples were antique bronze coins coated in silver (follis) dated in the Roman Empire period and were made during different rulers in different mints. While raw LIBS data revealed that in the period from the year 286 to 383 CE content of silver was constantly decreasing, the PCA showed that the samples can be somewhat grouped together based on their place of origin, which could be a useful hint when analysing unknown samples. It was also found that PCA can help in discriminating spectra corresponding to ablation from the surface and from the bulk. Furthermore, Partial Least Squares method (PLS) was used to obtain, based on a set of samples with known composition, an estimation of relative copper concentration in studied ancient coins. This analysis showed that copper concentration in surface layers ranged from 83% to 90%.

Once upon Multivariate Analyses: When They Tell Several Stories about Biological Evolution.

PubMed

Renaud, Sabrina; Dufour, Anne-Béatrice; Hardouin, Emilie A; Ledevin, Ronan; Auffray, Jean-Christophe

2015-01-01

Geometric morphometrics aims to characterize of the geometry of complex traits. It is therefore by essence multivariate. The most popular methods to investigate patterns of differentiation in this context are (1) the Principal Component Analysis (PCA), which is an eigenvalue decomposition of the total variance-covariance matrix among all specimens; (2) the Canonical Variate Analysis (CVA, a.k.a. linear discriminant analysis (LDA) for more than two groups), which aims at separating the groups by maximizing the between-group to within-group variance ratio; (3) the between-group PCA (bgPCA) which investigates patterns of between-group variation, without standardizing by the within-group variance. Standardizing within-group variance, as performed in the CVA, distorts the relationships among groups, an effect that is particularly strong if the variance is similarly oriented in a comparable way in all groups. Such shared direction of main morphological variance may occur and have a biological meaning, for instance corresponding to the most frequent standing genetic variation in a population. Here we undertake a case study of the evolution of house mouse molar shape across various islands, based on the real dataset and simulations. We investigated how patterns of main variance influence the depiction of among-group differentiation according to the interpretation of the PCA, bgPCA and CVA. Without arguing about a method performing 'better' than another, it rather emerges that working on the total or between-group variance (PCA and bgPCA) will tend to put the focus on the role of direction of main variance as line of least resistance to evolution. Standardizing by the within-group variance (CVA), by dampening the expression of this line of least resistance, has the potential to reveal other relevant patterns of differentiation that may otherwise be blurred.

Decreased expression of serine protease inhibitor family G1 (SERPING1) in prostate cancer can help distinguish high-risk prostate cancer and predicts malignant progression.

PubMed

Peng, Shengmeng; Du, Tao; Wu, Wanhua; Chen, Xianju; Lai, Yiming; Zhu, Dingjun; Wang, Qiong; Ma, Xiaoming; Lin, Chunhao; Li, Zean; Guo, Zhenghui; Huang, Hai

2018-06-11

The aim of this study was to investigate the associations of serine proteinase inhibitor family G1 (SERPING1) down-regulation with poor prognosis in patients with prostate cancer (PCa). Furthermore, we aim to find more novel and effective PCa molecular markers to provide an early screening of PCa, distinguish patients with aggressive PCa, predict the prognosis, or reduce the economic burden of PCa. SERPING1 protein expression in both human PCa and normal prostate tissues was detected by immunohistochemical staining, which intensity was analyzed in association with clinical pathological parameters such Gleason score, pathological grade, clinical stage, tumor stage, lymph node metastasis, and distant metastasis. Moreover, we used The Cancer Genome Atlas (TCGA) Database, Taylor Database, and Oncomine dataset to validate our immunohistochemical results and investigated the value of SERPING1 in PCa at mRNA level. Kaplan-Meier analysis and Cox regression analysis were performed to evaluate the relationship between SERPING1 and prognosis of patients with PCa. The outcome showed that SERPING1 was expressed mainly in cytoplasm of grand cells of prostate tissue and was significantly expressed less in PCa (P<0.001). Furthermore, in the tissue microarray of our samples, decreasing expression of SERPING1 was correlated with the higher Gleason score (P = 0.004), the higher pathological grade (P = 0.01) and the advanced tumor stage (P = 0.005) at protein level. In TCGA dataset and Taylor Dataset, low-expressed SERPING1 was correlated with the younger patient (P = 0.02 in TCGA, P = 0.044 in Taylor) and the higher Gleason score (P = 0.019 in TCGA, P<0.001 in Taylor) at mRNA level. Kaplan-Meier analysis revealed that the lower mRNA of SERPING1 predicted lower overall survivals (P = 0.027 in TCGA), lower disease-free survival (P = 0.029) and lower biochemical recurrence-free survival (P = 0.011 in Taylor). Data from Oncomine database shown that SERPING1 low expression implying higher malignancy of prostate lesions. Using multivariate analysis, we also found that SERPING1 expression was independent prognostic marker of poor disease-free survival and biochemical recurrence-free survival. SERPING1 may play an important role in PCa and can be serve as a novel marker in diagnosis and prognostic prediction in PCa. In addition, levels of SERPING1 can help identify low-risk prostate to provide reference for patients with PCa to accept active surveillance and reduce overtreatment. Copyright © 2018 Elsevier Inc. All rights reserved.

Characterizing the molecular features of ERG-positive tumors in primary and castration resistant prostate cancer

PubMed Central

Roudier, Martine P; Winters, Brian R; Coleman, Ilsa; Lam, Hung-Ming; Zhang, Xiaotun; Coleman, Roger; Chéry, Lisly; True, Lawrence D.; Higano, Celestia S.; Montgomery, Bruce; Lange, Paul H.; Snyder, Linda A.; Srivistava, Shiv; Corey, Eva; Vessella, Robert L.; Nelson, Peter S.; Üren, Aykut; Morrissey, Colm

2017-01-01

Background The TMPRSS2-ERG gene fusion is detected in approximately half of primary prostate cancers (PCa) yet the prognostic significance remains unclear. We hypothesized that ERG promotes the expression of common genes in primary PCa and metastatic castration-resistant PCa (CRPC), with the objective of identifying ERG-associated pathways, which may promote the transition from primary PCa to CRPC. Methods We constructed tissue microarrays (TMA) from 127 radical prostatectomy specimens, 20 LuCaP patient-derived xenografts (PDX), and 152 CRPC metastases obtained immediately at time of death. Nuclear ERG was assessed by immunohistochemistry (IHC). To characterize the molecular features of ERG-expressing PCa, a subset of IHC confirmed ERG+ or ERG-specimens including 11 radical prostatectomies, 20 LuCaP PDXs, and 45 CRPC metastases underwent gene expression analysis. Genes were ranked based on expression in primary PCa and CRPC. Common genes of interest were targeted for IHC analysis and expression compared with biochemical recurrence (BCR) status. Results IHC revealed that 43% of primary PCa, 35% of the LuCaP PDXs, and 18% of the CRPC metastases were ERG+ (12 of 48 patients [25%] had at least 1 ERG+ metastasis). Based on gene expression data and previous literature, two proteins involved in calcium signaling (NCALD, CACNA1D), a protein involved in inflammation (HLA-DMB), CD3 positive immune cells, and a novel ERG-associated protein, DCLK1 were evaluated in primary PCa and CRPC metastases. In ERG+ primary PCa, a weak association was seen with NCALD and CACNA1D protein expression. HLA-DMB expression and the presence of CD3 positive immune cells were decreased in CRPC metastases compared to primary PCa. DCLK1 was upregulated at the protein level in unpaired ERG+ primary PCa and CRPC metastases (p=0.0013 and p<0.0001, respectively). In primary PCa, ERG status or expression of targeted proteins was not associated with BCR-free survival. However for primary PCa, ERG+DCLK1+ patients exhibited shorter time to BCR (p=0.06) compared with ERG+DCLK1- patients. Conclusions This study examined ERG expression in primary PCa and CRPC. We have identified altered levels of inflammatory mediators associated with ERG expression. We determined expression of DCLK1 correlates with ERG expression and may play a role in primary PCa progression to metastatic CPRC. PMID:26990456

Identification and suppression of the p-coumaroyl CoA:hydroxycinnamyl alcohol transferase in Zea mays L.

PubMed Central

Marita, Jane M; Hatfield, Ronald D; Rancour, David M; Frost, Kenneth E

2014-01-01

Grasses, such as Zea mays L. (maize), contain relatively high levels of p-coumarates (pCA) within their cell walls. Incorporation of pCA into cell walls is believed to be due to a hydroxycinnamyl transferase that couples pCA to monolignols. To understand the role of pCA in maize development, the p-coumaroyl CoA:hydroxycinnamyl alcohol transferase (pCAT) was isolated and purified from maize stems. Purified pCAT was subjected to partial trypsin digestion, and peptides were sequenced by tandem mass spectrometry. TBLASTN analysis of the acquired peptide sequences identified a single full-length maize cDNA clone encoding all the peptide sequences obtained from the purified enzyme. The cDNA clone was obtained and used to generate an RNAi construct for suppressing pCAT expression in maize. Here we describe the effects of suppression of pCAT in maize. Primary screening of transgenic maize seedling leaves using a new rapid analytical platform was used to identify plants with decreased amounts of pCA. Using this screening method, mature leaves from fully developed plants were analyzed, confirming reduced pCA levels throughout plant development. Complete analysis of isolated cell walls from mature transgenic stems and leaves revealed that lignin levels did not change, but pCA levels decreased and the lignin composition was altered. Transgenic plants with the lowest levels of pCA had decreased levels of syringyl units in the lignin. Thus, altering the levels of pCAT expression in maize leads to altered lignin composition, but does not appear to alter the total amount of lignin present in the cell walls. PMID:24654730

Identification and suppression of the p-coumaroyl CoA:hydroxycinnamyl alcohol transferase in Zea mays L.

PubMed

Marita, Jane M; Hatfield, Ronald D; Rancour, David M; Frost, Kenneth E

2014-06-01

Grasses, such as Zea mays L. (maize), contain relatively high levels of p-coumarates (pCA) within their cell walls. Incorporation of pCA into cell walls is believed to be due to a hydroxycinnamyl transferase that couples pCA to monolignols. To understand the role of pCA in maize development, the p-coumaroyl CoA:hydroxycinnamyl alcohol transferase (pCAT) was isolated and purified from maize stems. Purified pCAT was subjected to partial trypsin digestion, and peptides were sequenced by tandem mass spectrometry. TBLASTN analysis of the acquired peptide sequences identified a single full-length maize cDNA clone encoding all the peptide sequences obtained from the purified enzyme. The cDNA clone was obtained and used to generate an RNAi construct for suppressing pCAT expression in maize. Here we describe the effects of suppression of pCAT in maize. Primary screening of transgenic maize seedling leaves using a new rapid analytical platform was used to identify plants with decreased amounts of pCA. Using this screening method, mature leaves from fully developed plants were analyzed, confirming reduced pCA levels throughout plant development. Complete analysis of isolated cell walls from mature transgenic stems and leaves revealed that lignin levels did not change, but pCA levels decreased and the lignin composition was altered. Transgenic plants with the lowest levels of pCA had decreased levels of syringyl units in the lignin. Thus, altering the levels of pCAT expression in maize leads to altered lignin composition, but does not appear to alter the total amount of lignin present in the cell walls. © 2014 The Authors The Plant Journal © 2014 John Wiley & Sons Ltd.

Prediction of BP reactivity to talking using hybrid soft computing approaches.

PubMed

Kaur, Gurmanik; Arora, Ajat Shatru; Jain, Vijender Kumar

2014-01-01

High blood pressure (BP) is associated with an increased risk of cardiovascular diseases. Therefore, optimal precision in measurement of BP is appropriate in clinical and research studies. In this work, anthropometric characteristics including age, height, weight, body mass index (BMI), and arm circumference (AC) were used as independent predictor variables for the prediction of BP reactivity to talking. Principal component analysis (PCA) was fused with artificial neural network (ANN), adaptive neurofuzzy inference system (ANFIS), and least square-support vector machine (LS-SVM) model to remove the multicollinearity effect among anthropometric predictor variables. The statistical tests in terms of coefficient of determination (R (2)), root mean square error (RMSE), and mean absolute percentage error (MAPE) revealed that PCA based LS-SVM (PCA-LS-SVM) model produced a more efficient prediction of BP reactivity as compared to other models. This assessment presents the importance and advantages posed by PCA fused prediction models for prediction of biological variables.

Dietary protocatechuic acid ameliorates dextran sulphate sodium-induced ulcerative colitis and hepatotoxicity in rats.

PubMed

Farombi, Ebenezer O; Adedara, Isaac A; Awoyemi, Omolola V; Njoku, Chinonye R; Micah, Gabriel O; Esogwa, Cynthia U; Owumi, Solomon E; Olopade, James O

2016-02-01

The present study investigated the antioxidant and anti-inflammatory effects of dietary protocatechuic acid (PCA), a simple hydrophilic phenolic compound commonly found in many edible vegetables, on dextran sulphate sodium (DSS)-induced ulcerative colitis and its associated hepatotoxicity in rats. PCA was administered orally at 10 mg kg(-1) to dextran sulphate sodium exposed rats for five days. The result revealed that administration of PCA significantly (p < 0.05) prevented the incidence of diarrhea and bleeding, the decrease in the body weight gain, shortening of colon length and the increase in colon mass index in DSS-treated rats. Furthermore, PCA prevented the increase in the plasma levels of pro-inflammatory cytokines, markers of liver toxicity and markedly suppressed the DSS-mediated elevation in colonic nitric oxide concentration and myeloperoxidase activity in the treated rats. Administration of PCA significantly protected against colonic and hepatic oxidative damage by increasing the antioxidant status and concomitantly decreased hydrogen peroxide and lipid peroxidation levels in the DSS-treated rats. Moreover, histological examinations confirmed PCA chemoprotection against colon and liver damage. Immunohistochemical analysis showed that PCA significantly inhibited cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS) protein expression in the colon of DSS-treated rats. In conclusion, the effective chemoprotective role of PCA in colitis and the associated hepatotoxicity is related to its intrinsic anti-inflammatory and anti-oxidative properties.

Germline Mutations in ATM and BRCA1/2 Distinguish Risk for Lethal and Indolent Prostate Cancer and are Associated with Early Age at Death

PubMed Central

Na, Rong; Zheng, S. Lilly; Han, Misop; Yu, Hongjie; Jiang, Deke; Shah, Sameep; Ewing, Charles M.; Zhang, Liti; Novakovic, Kristian; Petkewicz, Jacqueline; Gulukota, Kamalakar; Helseth, Donald L.; Quinn, Margo; Humphries, Elizabeth; Wiley, Kathleen E.; Isaacs, Sarah D.; Wu, Yishuo; Liu, Xu; Zhang, Ning; Wang, Chi-Hsiung; Khandekar, Janardan; Hulick, Peter J.; Shevrin, Daniel H.; Cooney, Kathleen A.; Shen, Zhoujun; Partin, Alan W.; Carter, H. Ballentine; Carducci, Michael A.; Eisenberger, Mario A.; Denmeade, Sam R.; McGuire, Michael; Walsh, Patrick C.; Helfand, Brian T.; Brendler, Charles B.; Ding, Qiang; Xu, Jianfeng; Isaacs, William B.

2017-01-01

Background Germline mutations in BRCA1/2 and ATM have been associated with prostate cancer (PCa) risk. Objective To directly assess whether germline mutations in these three genes distinguish lethal from indolent PCa and whether they confer any effect on age at death. Design, setting, and participants A retrospective case-case study of 313 patients who died of PCa and 486 patients with low-risk localized PCa of European, African, and Chinese descent. Germline DNA of each of the 799 patients was sequenced for these three genes. Outcome measurements and statistical analysis Mutation carrier rates and their effect on lethal PCa were analyzed using the Fisher’s exact test and Cox regression analysis, respectively. Results and limitations The combined BRCA1/2 and ATM mutation carrier rate was significantly higher in lethal PCa patients (6.07%) than localized PCa patients (1.44%), p = 0.0007. The rate also differed significantly among lethal PCa patients as a function of age at death (10.00%, 9.08%, 8.33%, 4.94%, and 2.97% in patients who died ≤60 yr, 61–65 yr, 66–70 yr, 71–75 yr, and over 75 yr, respectively, p = 0.046) and time to death after diagnosis (12.26%, 4.76%, and 0.98% in patients who died ≤5 yr, 6–10 yr, and > 10 yr after a PCa diagnosis, respectively, p = 0.0006). Survival analysis in the entire cohort revealed mutation carriers remained an independent predictor of lethal PCa after adjusting for race and age, prostate-specific antigen, and Gleason score at the time of diagnosis (hazard ratio = 2.13, 95% confidence interval: 1.24–3.66, p = 0.004). A limitation of this study is that other DNA repair genes were not analyzed. Conclusions Mutation status of BRCA1/2 and ATM distinguishes risk for lethal and indolent PCa and is associated with earlier age at death and shorter survival time. Patient summary Prostate cancer patients with inherited mutations in BRCA1/2 and ATM are more likely to die of prostate cancer and do so at an earlier age. PMID:27989354

68Ga-HBED-CC-PSMA PET/CT Versus Histopathology in Primary Localized Prostate Cancer: A Voxel-Wise Comparison

PubMed Central

Zamboglou, Constantinos; Schiller, Florian; Fechter, Tobias; Wieser, Gesche; Jilg, Cordula Annette; Chirindel, Alin; Salman, Nasr; Drendel, Vanessa; Werner, Martin; Mix, Michael; Meyer, Philipp Tobias; Grosu, Anca Ligia

2016-01-01

Purpose: We performed a voxel-wise comparison of 68Ga-HBED-CC-PSMA PET/CT with prostate histopathology to evaluate the performance of 68Ga-HBED-CC-PSMA for the detection and delineation of primary prostate cancer (PCa). Methodology: Nine patients with histopathological proven primary PCa underwent 68Ga-HBED-CC-PSMA PET/CT followed by radical prostatectomy. Resected prostates were scanned by ex-vivo CT in a special localizer and histopathologically prepared. Histopathological information was matched to ex-vivo CT. PCa volume (PCa-histo) and non-PCa tissue in the prostate (NPCa-histo) were processed to obtain a PCa-model, which was adjusted to PET-resolution (histo-PET). Each histo-PET was coregistered to in-vivo PSMA-PET/CT data. Results: Analysis of spatial overlap between histo-PET and PSMA PET revealed highly significant correlations (p < 10-5) in nine patients and moderate to high coefficients of determination (R²) from 42 to 82 % with an average of 60 ± 14 % in eight patients (in one patient R2 = 7 %). Mean SUVmean in PCa-histo and NPCa-histo was 5.6 ± 6.1 and 3.3 ± 2.5 (p = 0.012). Voxel-wise receiver-operating characteristic (ROC) analyses comparing the prediction by PSMA-PET with the non-smoothed tumor distribution from histopathology yielded an average area under the curve of 0.83 ± 0.12. Absolute and relative SUV (normalized to SUVmax) thresholds for achieving at least 90 % sensitivity were 3.19 ± 3.35 and 0.28 ± 0.09, respectively. Conclusions: Voxel-wise analyses revealed good correlations of 68Ga-HBED-CC-PSMA PET/CT and histopathology in eight out of nine patients. Thus, PSMA-PET allows a reliable detection and delineation of PCa as basis for PET-guided focal therapies. PMID:27446496

A genetic variant in SLC28A3, rs56350726, is associated with progression to castration-resistant prostate cancer in a Korean population with metastatic prostate cancer.

PubMed

Jo, Jung Ku; Oh, Jong Jin; Kim, Yong Tae; Moon, Hong Sang; Choi, Hong Yong; Park, Seunghyun; Ho, Jin-Nyoung; Yoon, Sungroh; Park, Hae Young; Byun, Seok-Soo

2017-11-14

Genetic variation which related with progression to castration-resistant prostate cancer (CRPC) during androgen-deprivation therapy (ADT) has not been elucidated in patients with metastatic prostate cancer (mPCa). Therefore, we assessed the association between genetic variats in mPCa and progession to CRPC. Analysis of exome genotypes revealed that 42 SNPs were significantly associated with mPCa. The top five polymorphisms were statistically significantly associated with metastatic disease. In addition, one of these SNPs, rs56350726, was significantly associated with time to CRPC in Kaplan-Meier analysis (Log-rank test, p = 0.011). In multivariable Cox regression, rs56350726 was strongly associated with progression to CRPC (HR = 4.172 95% CI = 1.223-14.239, p = 0.023). We assessed genetic variation among 1000 patients with PCa with or without metastasis, using 242,221 single nucleotide polymorphisms (SNPs) on the custom HumanExome BeadChip v1.0 (Illuminam Inc.). We analyzed the time to CRPC in 110 of the 1000 patients who were treated with ADT. Genetic data were analyzed using unconditional logistic regression and odds ratios calculated as estimates of relative risk of metastasis. We identified SNPs associated with metastasis and analyzed the relationship between these SNPs and time to CRPC in mPCa. Based on a genetic variation, the five top SNPs were observed to associate with mPCa. And one (SLC28A3, rs56350726) of five SNP was found the association with the progression to CRPC in patients with mPCa.

The Raman spectrum character of skin tumor induced by UVB

NASA Astrophysics Data System (ADS)

Wu, Shulian; Hu, Liangjun; Wang, Yunxia; Li, Yongzeng

2016-03-01

In our study, the skin canceration processes induced by UVB were analyzed from the perspective of tissue spectrum. A home-made Raman spectral system with a millimeter order excitation laser spot size combined with a multivariate statistical analysis for monitoring the skin changed irradiated by UVB was studied and the discrimination were evaluated. Raman scattering signals of the SCC and normal skin were acquired. Spectral differences in Raman spectra were revealed. Linear discriminant analysis (LDA) based on principal component analysis (PCA) were employed to generate diagnostic algorithms for the classification of skin SCC and normal. The results indicated that Raman spectroscopy combined with PCA-LDA demonstrated good potential for improving the diagnosis of skin cancers.

Variability search in M 31 using principal component analysis and the Hubble Source Catalogue

NASA Astrophysics Data System (ADS)

Moretti, M. I.; Hatzidimitriou, D.; Karampelas, A.; Sokolovsky, K. V.; Bonanos, A. Z.; Gavras, P.; Yang, M.

2018-06-01

Principal component analysis (PCA) is being extensively used in Astronomy but not yet exhaustively exploited for variability search. The aim of this work is to investigate the effectiveness of using the PCA as a method to search for variable stars in large photometric data sets. We apply PCA to variability indices computed for light curves of 18 152 stars in three fields in M 31 extracted from the Hubble Source Catalogue. The projection of the data into the principal components is used as a stellar variability detection and classification tool, capable of distinguishing between RR Lyrae stars, long-period variables (LPVs) and non-variables. This projection recovered more than 90 per cent of the known variables and revealed 38 previously unknown variable stars (about 30 per cent more), all LPVs except for one object of uncertain variability type. We conclude that this methodology can indeed successfully identify candidate variable stars.

Evaluation of Staining-Dependent Colour Changes in Resin Composites Using Principal Component Analysis

PubMed Central

Manojlovic, D.; Lenhardt, L.; Milićević, B.; Antonov, M.; Miletic, V.; Dramićanin, M. D.

2015-01-01

Colour changes in Gradia Direct™ composite after immersion in tea, coffee, red wine, Coca-Cola, Colgate mouthwash, and distilled water were evaluated using principal component analysis (PCA) and the CIELAB colour coordinates. The reflection spectra of the composites were used as input data for the PCA. The output data (scores and loadings) provided information about the magnitude and origin of the surface reflection changes after exposure to the staining solutions. The reflection spectra of the stained samples generally exhibited lower reflection in the blue spectral range, which was manifested in the lower content of the blue shade for the samples. Both analyses demonstrated the high staining abilities of tea, coffee, and red wine, which produced total colour changes of 4.31, 6.61, and 6.22, respectively, according to the CIELAB analysis. PCA revealed subtle changes in the reflection spectra of composites immersed in Coca-Cola, demonstrating Coca-Cola’s ability to stain the composite to a small degree. PMID:26450008

Evaluation of Staining-Dependent Colour Changes in Resin Composites Using Principal Component Analysis.

PubMed

Manojlovic, D; Lenhardt, L; Milićević, B; Antonov, M; Miletic, V; Dramićanin, M D

2015-10-09

Colour changes in Gradia Direct™ composite after immersion in tea, coffee, red wine, Coca-Cola, Colgate mouthwash, and distilled water were evaluated using principal component analysis (PCA) and the CIELAB colour coordinates. The reflection spectra of the composites were used as input data for the PCA. The output data (scores and loadings) provided information about the magnitude and origin of the surface reflection changes after exposure to the staining solutions. The reflection spectra of the stained samples generally exhibited lower reflection in the blue spectral range, which was manifested in the lower content of the blue shade for the samples. Both analyses demonstrated the high staining abilities of tea, coffee, and red wine, which produced total colour changes of 4.31, 6.61, and 6.22, respectively, according to the CIELAB analysis. PCA revealed subtle changes in the reflection spectra of composites immersed in Coca-Cola, demonstrating Coca-Cola's ability to stain the composite to a small degree.

Principal component analysis of indocyanine green fluorescence dynamics for diagnosis of vascular diseases

NASA Astrophysics Data System (ADS)

Seo, Jihye; An, Yuri; Lee, Jungsul; Choi, Chulhee

2015-03-01

Indocyanine green (ICG), a near-infrared fluorophore, has been used in visualization of vascular structure and non-invasive diagnosis of vascular disease. Although many imaging techniques have been developed, there are still limitations in diagnosis of vascular diseases. We have recently developed a minimally invasive diagnostics system based on ICG fluorescence imaging for sensitive detection of vascular insufficiency. In this study, we used principal component analysis (PCA) to examine ICG spatiotemporal profile and to obtain pathophysiological information from ICG dynamics. Here we demonstrated that principal components of ICG dynamics in both feet showed significant differences between normal control and diabetic patients with vascula complications. We extracted the PCA time courses of the first three components and found distinct pattern in diabetic patient. We propose that PCA of ICG dynamics reveal better classification performance compared to fluorescence intensity analysis. We anticipate that specific feature of spatiotemporal ICG dynamics can be useful in diagnosis of various vascular diseases.

Biotransformation of ferulic acid to protocatechuic acid by Corynebacterium glutamicum ATCC 21420 engineered to express vanillate O-demethylase.

PubMed

Okai, Naoko; Masuda, Takaya; Takeshima, Yasunobu; Tanaka, Kosei; Yoshida, Ken-Ichi; Miyamoto, Masanori; Ogino, Chiaki; Kondo, Akihiko

2017-12-01

Ferulic acid (4-hydroxy-3-methoxycinnamic acid, FA) is a lignin-derived phenolic compound abundant in plant biomass. The utilization of FA and its conversion to valuable compounds is desired. Protocatechuic acid (3,4-dihydroxybenzoic acid, PCA) is a precursor of polymers and plastics and a constituent of food. A microbial conversion system to produce PCA from FA was developed in this study using a PCA-producing strain of Corynebacterium glutamicum F (ATCC 21420). C. glutamicum strain F grown at 30 °C for 48 h utilized 2 mM each of FA and vanillic acid (4-hydroxy-3-methoxybenzoic acid, VA) to produce PCA, which was secreted into the medium. FA may be catabolized by C. glutamicum through proposed (I) non-β-oxidative, CoA-dependent or (II) β-oxidative, CoA-dependent phenylpropanoid pathways. The conversion of VA to PCA is the last step in each pathway. Therefore, the vanillate O-demethylase gene (vanAB) from Corynebacterium efficiens NBRC 100395 was expressed in C. glutamicum F (designated strain FVan) cultured at 30 °C in AF medium containing FA. Strain C. glutamicum FVan converted 4.57 ± 0.07 mM of FA into 2.87 ± 0.01 mM PCA after 48 h with yields of 62.8% (mol/mol), and 6.91 mM (1064 mg/L) of PCA was produced from 16.0 mM of FA after 12 h of fed-batch biotransformation. Genomic analysis of C. glutamicum ATCC 21420 revealed that the PCA-utilization genes (pca cluster) were conserved in strain ATCC 21420 and that mutations were present in the PCA importer gene pcaK.

Characterizing the molecular features of ERG-positive tumors in primary and castration resistant prostate cancer.

PubMed

Roudier, Martine P; Winters, Brian R; Coleman, Ilsa; Lam, Hung-Ming; Zhang, Xiaotun; Coleman, Roger; Chéry, Lisly; True, Lawrence D; Higano, Celestia S; Montgomery, Bruce; Lange, Paul H; Snyder, Linda A; Srivastava, Shiv; Corey, Eva; Vessella, Robert L; Nelson, Peter S; Üren, Aykut; Morrissey, Colm

2016-06-01

The TMPRSS2-ERG gene fusion is detected in approximately half of primary prostate cancers (PCa) yet the prognostic significance remains unclear. We hypothesized that ERG promotes the expression of common genes in primary PCa and metastatic castration-resistant PCa (CRPC), with the objective of identifying ERG-associated pathways, which may promote the transition from primary PCa to CRPC. We constructed tissue microarrays (TMA) from 127 radical prostatectomy specimens, 20 LuCaP patient-derived xenografts (PDX), and 152 CRPC metastases obtained immediately at time of death. Nuclear ERG was assessed by immunohistochemistry (IHC). To characterize the molecular features of ERG-expressing PCa, a subset of IHC confirmed ERG+ or ERG- specimens including 11 radical prostatectomies, 20 LuCaP PDXs, and 45 CRPC metastases underwent gene expression analysis. Genes were ranked based on expression in primary PCa and CRPC. Common genes of interest were targeted for IHC analysis and expression compared with biochemical recurrence (BCR) status. IHC revealed that 43% of primary PCa, 35% of the LuCaP PDXs, and 18% of the CRPC metastases were ERG+ (12 of 48 patients [25%] had at least one ERG+ metastasis). Based on gene expression data and previous literature, two proteins involved in calcium signaling (NCALD, CACNA1D), a protein involved in inflammation (HLA-DMB), CD3 positive immune cells, and a novel ERG-associated protein, DCLK1 were evaluated in primary PCa and CRPC metastases. In ERG+ primary PCa, a weak association was seen with NCALD and CACNA1D protein expression. HLA-DMB association with ERG was decreased and CD3 cell number association with ERG was changed from positive to negative in CRPC metastases compared to primary PCa. DCLK1 was upregulated at the protein level in unpaired ERG+ primary PCa and CRPC metastases (P = 0.0013 and P < 0.0001, respectively). In primary PCa, ERG status or expression of targeted proteins was not associated with BCR-free survival. However, for primary PCa, ERG+DCLK1+ patients exhibited shorter time to BCR (P = 0.06) compared with ERG+DCLK1- patients. This study examined ERG expression in primary PCa and CRPC. We have identified altered levels of inflammatory mediators associated with ERG expression. We determined expression of DCLK1 correlates with ERG expression and may play a role in primary PCa progression to metastatic CPRC. Prostate 76:810-822, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Decision analysis for a data collection system of patient-controlled analgesia with a multi-attribute utility model.

PubMed

Lee, I-Jung; Huang, Shih-Yu; Tsou, Mei-Yung; Chan, Kwok-Hon; Chang, Kuang-Yi

2010-10-01

Data collection systems are very important for the practice of patient-controlled analgesia (PCA). This study aimed to evaluate 3 PCA data collection systems and selected the most favorable system with the aid of multiattribute utility (MAU) theory. We developed a questionnaire with 10 items to evaluate the PCA data collection system and 1 item for overall satisfaction based on MAU theory. Three systems were compared in the questionnaire, including a paper record, optic card reader and personal digital assistant (PDA). A pilot study demonstrated a good internal and test-retest reliability of the questionnaire. A weighted utility score combining the relative importance of individual items assigned by each participant and their responses to each question was calculated for each system. Sensitivity analyses with distinct weighting protocols were conducted to evaluate the stability of the final results. Thirty potential users of a PCA data collection system were recruited in the study. The item "easy to use" had the highest median rank and received the heaviest mean weight among all items. MAU analysis showed that the PDA system had a higher utility score than that in the other 2 systems. Sensitivity analyses revealed that both inverse and reciprocal weighting processes favored the PDA system. High correlations between overall satisfaction and MAU scores from miscellaneous weighting protocols suggested a good predictive validity of our MAU-based questionnaire. The PDA system was selected as the most favorable PCA data collection system by the MAU analysis. The item "easy to use" was the most important attribute of the PCA data collection system. MAU theory can evaluate alternatives by taking into account individual preferences of stakeholders and aid in better decision-making. Copyright © 2010 Elsevier. Published by Elsevier B.V. All rights reserved.

Proteomic Comparison and MRM-Based Comparative Analysis of Metabolites Reveal Metabolic Shift in Human Prostate Cancer Cell Lines.

PubMed

Shu, Qingbo; Cai, Tanxi; Chen, Xiulan; Zhu, Helen He; Xue, Peng; Zhu, Nali; Xie, Zhensheng; Wei, Shasha; Zhang, Qing; Niu, Lili; Gao, Wei-Qiang; Yang, Fuquan

2015-08-07

One of the major challenges in prostate cancer therapy remains the development of effective treatments for castration-resistant prostate cancer (CRPC), as the underlying mechanisms for its progression remain elusive. Previous studies showed that androgen receptor (AR) is crucially involved in regulation of metabolism in prostate cancer (PCa) cells throughout the transition from early stage, androgen-sensitive PCa to androgen-independent CRPC. AR achieves such metabolic rewiring directively either via its transcriptional activity or via interactions with AMP-activated protein kinase (AMPK). However, due to the heterogeneous expression and activity status of AR in PCa cells, it remains a challenge to investigate the links between AR status and metabolic alterations. To this end, we compared the proteomes of three pairs of androgen-sensitive (AS) and androgen-independent (AI) PCa cell lines, namely, PC3-AR(+)/PC3, 22Rv1/Du145, and LNCaP/C42B, using an iTRAQ labeling approach. Our results revealed that most of the differentially expressed proteins between each pair function in metabolism, indicating a metabolic shift between AS and AI cells, as further validated by multiple reaction monitoring (MRM)-based quantification of nucleotides and relative comparison of fatty acids between these cell lines. Furthermore, increased adenylate kinase isoenzyme 1 (AK1) in AS relative to AI cells may result in activation of AMPK, representing a major regulatory factor involved in the observed metabolic shift in PCa cells.

PHI and PCA3 improve the prognostic performance of PRIAS and Epstein criteria in predicting insignificant prostate cancer in men eligible for active surveillance.

PubMed

Cantiello, Francesco; Russo, Giorgio Ivan; Cicione, Antonio; Ferro, Matteo; Cimino, Sebastiano; Favilla, Vincenzo; Perdonà, Sisto; De Cobelli, Ottavio; Magno, Carlo; Morgia, Giuseppe; Damiano, Rocco

2016-04-01

To assess the performance of prostate health index (PHI) and prostate cancer antigen 3 (PCA3) when added to the PRIAS or Epstein criteria in predicting the presence of pathologically insignificant prostate cancer (IPCa) in patients who underwent radical prostatectomy (RP) but eligible for active surveillance (AS). An observational retrospective study was performed in 188 PCa patients treated with laparoscopic or robot-assisted RP but eligible for AS according to Epstein or PRIAS criteria. Blood and urinary specimens were collected before initial prostate biopsy for PHI and PCA3 measurements. Multivariate logistic regression analyses and decision curve analysis were carried out to identify predictors of IPCa using the updated ERSPC definition. At the multivariate analyses, the inclusion of both PCA3 and PHI significantly increased the accuracy of the Epstein multivariate model in predicting IPCa with an increase of 17 % (AUC = 0.77) and of 32 % (AUC = 0.92), respectively. The inclusion of both PCA3 and PHI also increased the predictive accuracy of the PRIAS multivariate model with an increase of 29 % (AUC = 0.87) and of 39 % (AUC = 0.97), respectively. DCA revealed that the multivariable models with the addition of PHI or PCA3 showed a greater net benefit and performed better than the reference models. In a direct comparison, PHI outperformed PCA3 performance resulting in higher net benefit. In a same cohort of patients eligible for AS, the addition of PHI and PCA3 to Epstein or PRIAS models improved their prognostic performance. PHI resulted in greater net benefit in predicting IPCa compared to PCA3.

RankProd Combined with Genetic Algorithm Optimized Artificial Neural Network Establishes a Diagnostic and Prognostic Prediction Model that Revealed C1QTNF3 as a Biomarker for Prostate Cancer.

PubMed

Hou, Qi; Bing, Zhi-Tong; Hu, Cheng; Li, Mao-Yin; Yang, Ke-Hu; Mo, Zu; Xie, Xiang-Wei; Liao, Ji-Lin; Lu, Yan; Horie, Shigeo; Lou, Ming-Wu

2018-06-01

Prostate cancer (PCa) is the most commonly diagnosed cancer in males in the Western world. Although prostate-specific antigen (PSA) has been widely used as a biomarker for PCa diagnosis, its results can be controversial. Therefore, new biomarkers are needed to enhance the clinical management of PCa. From publicly available microarray data, differentially expressed genes (DEGs) were identified by meta-analysis with RankProd. Genetic algorithm optimized artificial neural network (GA-ANN) was introduced to establish a diagnostic prediction model and to filter candidate genes. The diagnostic and prognostic capability of the prediction model and candidate genes were investigated in both GEO and TCGA datasets. Candidate genes were further validated by qPCR, Western Blot and Tissue microarray. By RankProd meta-analyses, 2306 significantly up- and 1311 down-regulated probes were found in 133 cases and 30 controls microarray data. The overall accuracy rate of the PCa diagnostic prediction model, consisting of a 15-gene signature, reached up to 100% in both the training and test dataset. The prediction model also showed good results for the diagnosis (AUC = 0.953) and prognosis (AUC of 5 years overall survival time = 0.808) of PCa in the TCGA database. The expression levels of three genes, FABP5, C1QTNF3 and LPHN3, were validated by qPCR. C1QTNF3 high expression was further validated in PCa tissue by Western Blot and Tissue microarray. In the GEO datasets, C1QTNF3 was a good predictor for the diagnosis of PCa (GSE6956: AUC = 0.791; GSE8218: AUC = 0.868; GSE26910: AUC = 0.972). In the TCGA database, C1QTNF3 was significantly associated with PCa patient recurrence free survival (P < .001, AUC = 0.57). In this study, we have developed a diagnostic and prognostic prediction model for PCa. C1QTNF3 was revealed as a promising biomarker for PCa. This approach can be applied to other high-throughput data from different platforms for the discovery of oncogenes or biomarkers in different kinds of diseases. Copyright © 2018. Published by Elsevier B.V.

On a PCA-based lung motion model

NASA Astrophysics Data System (ADS)

Li, Ruijiang; Lewis, John H.; Jia, Xun; Zhao, Tianyu; Liu, Weifeng; Wuenschel, Sara; Lamb, James; Yang, Deshan; Low, Daniel A.; Jiang, Steve B.

2011-09-01

Respiration-induced organ motion is one of the major uncertainties in lung cancer radiotherapy and is crucial to be able to accurately model the lung motion. Most work so far has focused on the study of the motion of a single point (usually the tumor center of mass), and much less work has been done to model the motion of the entire lung. Inspired by the work of Zhang et al (2007 Med. Phys. 34 4772-81), we believe that the spatiotemporal relationship of the entire lung motion can be accurately modeled based on principle component analysis (PCA) and then a sparse subset of the entire lung, such as an implanted marker, can be used to drive the motion of the entire lung (including the tumor). The goal of this work is twofold. First, we aim to understand the underlying reason why PCA is effective for modeling lung motion and find the optimal number of PCA coefficients for accurate lung motion modeling. We attempt to address the above important problems both in a theoretical framework and in the context of real clinical data. Second, we propose a new method to derive the entire lung motion using a single internal marker based on the PCA model. The main results of this work are as follows. We derived an important property which reveals the implicit regularization imposed by the PCA model. We then studied the model using two mathematical respiratory phantoms and 11 clinical 4DCT scans for eight lung cancer patients. For the mathematical phantoms with cosine and an even power (2n) of cosine motion, we proved that 2 and 2n PCA coefficients and eigenvectors will completely represent the lung motion, respectively. Moreover, for the cosine phantom, we derived the equivalence conditions for the PCA motion model and the physiological 5D lung motion model (Low et al 2005 Int. J. Radiat. Oncol. Biol. Phys. 63 921-9). For the clinical 4DCT data, we demonstrated the modeling power and generalization performance of the PCA model. The average 3D modeling error using PCA was within 1 mm (0.7 ± 0.1 mm). When a single artificial internal marker was used to derive the lung motion, the average 3D error was found to be within 2 mm (1.8 ± 0.3 mm) through comprehensive statistical analysis. The optimal number of PCA coefficients needs to be determined on a patient-by-patient basis and two PCA coefficients seem to be sufficient for accurate modeling of the lung motion for most patients. In conclusion, we have presented thorough theoretical analysis and clinical validation of the PCA lung motion model. The feasibility of deriving the entire lung motion using a single marker has also been demonstrated on clinical data using a simulation approach.

MiR-145 detection in urinary extracellular vesicles increase diagnostic efficiency of prostate cancer based on hydrostatic filtration dialysis method.

PubMed

Xu, Yong; Qin, Sihua; An, Taixue; Tang, Yueting; Huang, Yiyao; Zheng, Lei

2017-07-01

Extracellular vesicles (EVs) can be detected in body fluids and may serve as disease biomarkers. Increasing evidence suggests that circulating miRNAs in serum and urine may be potential non-invasive biomarkers for prostate cancer (PCa). In the present study, we aimed to investigate whether hydrostatic filtration dialysis (HFD) is suitable for urinary EVs (UEVs) isolation and whether such reported PCa-related miRNAs can be detected in UEVs as PCa biomarkers. To analyze EVs miRNAs, we searched for an easy and economic method to enrich EVs from urine samples. We compared the efficiency of HFD method and conventional ultracentrifugation (UC) in isolating UEVs. Subsequently, UEVs were isolated from patients with PCa, patients with benign prostate hyperplasia (BPH) and healthy individuals. Differential expression of four PCa-related miRNAs (miR-572, miR-1290, miR-141, and miR-145) were measured in UEVs and paired serum EVs using SYBR Green-based quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The overall performance of HFD was similar to UC. In miRNA yield, both HFD and UC can meet the needs of further analysis. The level of miR-145 in UEVs was significantly increased in patients with PCa compared with the patients with BPH (P = 0.018). In addition, significant increase was observed in miR-145 levels when patients with Gleason score ≥8 tumors compared with Gleason score ≤7 (P = 0.020). Receiver-operating characteristic curve (ROC) revealed that miR-145 in UEVs combined with serum PSA could differentiate PCa from BPH better than PSA alone (AUC 0.863 and AUC 0.805, respectively). In serum EVs, four miRNAs were significantly higher in patients with PCa than with BPH. HFD is appropriate for UEVs isolation and miRNA analysis when compared with conventional UC. miR-145 in UEVs is upregulated from PCa patients compared BPH patients and healthy controls. We suggest the potential use of UEVs miR-145 as a biomarker of PCa. © 2017 Wiley Periodicals, Inc.

Characterizing Variability of Modular Brain Connectivity with Constrained Principal Component Analysis

PubMed Central

Hirayama, Jun-ichiro; Hyvärinen, Aapo; Kiviniemi, Vesa; Kawanabe, Motoaki; Yamashita, Okito

2016-01-01

Characterizing the variability of resting-state functional brain connectivity across subjects and/or over time has recently attracted much attention. Principal component analysis (PCA) serves as a fundamental statistical technique for such analyses. However, performing PCA on high-dimensional connectivity matrices yields complicated “eigenconnectivity” patterns, for which systematic interpretation is a challenging issue. Here, we overcome this issue with a novel constrained PCA method for connectivity matrices by extending the idea of the previously proposed orthogonal connectivity factorization method. Our new method, modular connectivity factorization (MCF), explicitly introduces the modularity of brain networks as a parametric constraint on eigenconnectivity matrices. In particular, MCF analyzes the variability in both intra- and inter-module connectivities, simultaneously finding network modules in a principled, data-driven manner. The parametric constraint provides a compact module-based visualization scheme with which the result can be intuitively interpreted. We develop an optimization algorithm to solve the constrained PCA problem and validate our method in simulation studies and with a resting-state functional connectivity MRI dataset of 986 subjects. The results show that the proposed MCF method successfully reveals the underlying modular eigenconnectivity patterns in more general situations and is a promising alternative to existing methods. PMID:28002474

Structured Sparse Principal Components Analysis With the TV-Elastic Net Penalty.

PubMed

de Pierrefeu, Amicie; Lofstedt, Tommy; Hadj-Selem, Fouad; Dubois, Mathieu; Jardri, Renaud; Fovet, Thomas; Ciuciu, Philippe; Frouin, Vincent; Duchesnay, Edouard

2018-02-01

Principal component analysis (PCA) is an exploratory tool widely used in data analysis to uncover the dominant patterns of variability within a population. Despite its ability to represent a data set in a low-dimensional space, PCA's interpretability remains limited. Indeed, the components produced by PCA are often noisy or exhibit no visually meaningful patterns. Furthermore, the fact that the components are usually non-sparse may also impede interpretation, unless arbitrary thresholding is applied. However, in neuroimaging, it is essential to uncover clinically interpretable phenotypic markers that would account for the main variability in the brain images of a population. Recently, some alternatives to the standard PCA approach, such as sparse PCA (SPCA), have been proposed, their aim being to limit the density of the components. Nonetheless, sparsity alone does not entirely solve the interpretability problem in neuroimaging, since it may yield scattered and unstable components. We hypothesized that the incorporation of prior information regarding the structure of the data may lead to improved relevance and interpretability of brain patterns. We therefore present a simple extension of the popular PCA framework that adds structured sparsity penalties on the loading vectors in order to identify the few stable regions in the brain images that capture most of the variability. Such structured sparsity can be obtained by combining, e.g., and total variation (TV) penalties, where the TV regularization encodes information on the underlying structure of the data. This paper presents the structured SPCA (denoted SPCA-TV) optimization framework and its resolution. We demonstrate SPCA-TV's effectiveness and versatility on three different data sets. It can be applied to any kind of structured data, such as, e.g., -dimensional array images or meshes of cortical surfaces. The gains of SPCA-TV over unstructured approaches (such as SPCA and ElasticNet PCA) or structured approach (such as GraphNet PCA) are significant, since SPCA-TV reveals the variability within a data set in the form of intelligible brain patterns that are easier to interpret and more stable across different samples.

Hypoxia on the Expression of Hepatoma Upregulated Protein in Prostate Cancer Cells

PubMed Central

Espinoza, Ingrid; Sakiyama, Marcelo J.; Ma, Tangeng; Fair, Logan; Zhou, Xinchun; Hassan, Mohamed; Zabaleta, Jovanny; Gomez, Christian R.

2016-01-01

Hepatoma upregulated protein (HURP) is a multifunctional protein with clinical promise. This protein has been demonstrated to be a predictive marker for the outcome in high-risk prostate cancer (PCa) patients, besides being a resistance factor in PCa. Although changes in oxygen tension (pO2) are associated with PCa aggressiveness, the role of hypoxia in the regulation of tumor progression genes such as HURP has not yet been described. We hypothesized that pO2 alteration is involved in the regulation of HURP expression in PCa cells. In the present study, PCa cells were incubated at 2% O2 (hypoxia) and 20% O2 (normoxia) conditions. Hypoxia reduced cell growth rate of PCa cells, when compared to the growth rate of cells cultured under normoxia (p < 0.05). The decrease in cell viability was accompanied by fivefold (p < 0.05) elevated rate of vascular endothelial growth factor (VEGF) release. The expression of VEGF and the hypoxia-inducible metabolic enzyme carbonic anhydrase 9 were elevated maximally nearly 61-fold and 200-fold, respectively (p < 0.05). Noted in two cell lines (LNCaP and C4-2B) and independent of the oxygen levels, HURP expression assessed at both mRNA and protein levels was reduced. However, the decrease was more pronounced in cells cultured under hypoxia (p < 0.05). Interestingly, the analysis of patients’ specimens by Western blot revealed a marked increase of HURP protein (fivefold), when compared to control (cystoprostatectomy) tissue (p < 0.05). Immunohistochemistry analysis showed an increase in the immunostaining intensity of HURP and the hypoxia-sensitive molecules, hypoxia-inducible factor 1-alpha (HIF-1α), VEGF, and heat-shock protein 60 (HSP60) in association with tumor grade. The data also suggested a redistribution of subcellular localization for HURP and HIF-1α from the nucleus to the cytoplasmic compartment in relation to increasing tumor grade. Analysis of HURP Promoter for HIF-1-binding sites revealed presence of four putative HIF binding sites on the promoter of DLGAP5/HURP gene in the non-translated region upstream from the start codon, suggesting association between HIF-1α and the regulation of HURP protein. Taken together, our findings suggest a modulatory role of hypoxia on the expression of HURP. Additionally our results provide basis for utilization of tumor-associated molecules as predictors of aggressive PCa. PMID:27379206

PTEN genomic deletion predicts prostate cancer recurrence and is associated with low AR expression and transcriptional activity

PubMed Central

2012-01-01

Background Prostate cancer (PCa), a leading cause of cancer death in North American men, displays a broad range of clinical outcome from relatively indolent to lethal metastatic disease. Several genomic alterations have been identified in PCa which may serve as predictors of progression. PTEN, (10q23.3), is a negative regulator of the phosphatidylinositol 3-kinase (PIK3)/AKT survival pathway and a tumor suppressor frequently deleted in PCa. The androgen receptor (AR) signalling pathway is known to play an important role in PCa and its blockade constitutes a commonly used treatment modality. In this study, we assessed the deletion status of PTEN along with AR expression levels in 43 primary PCa specimens with clinical follow-up. Methods Fluorescence In Situ Hybridization (FISH) was done on formalin fixed paraffin embedded (FFPE) PCa samples to examine the deletion status of PTEN. AR expression levels were determined using immunohistochemistry (IHC). Results Using FISH, we found 18 cases of PTEN deletion. Kaplan-Meier analysis showed an association with disease recurrence (P=0.03). Concurrently, IHC staining for AR found significantly lower levels of AR expression within those tumors deleted for PTEN (P<0.05). To validate these observations we interrogated a copy number alteration and gene expression profiling dataset of 64 PCa samples, 17 of which were PTEN deleted. We confirmed the predictive value of PTEN deletion in disease recurrence (P=0.03). PTEN deletion was also linked to diminished expression of PTEN (P<0.01) and AR (P=0.02). Furthermore, gene set enrichment analysis revealed a diminished expression of genes downstream of AR signalling in PTEN deleted tumors. Conclusions Altogether, our data suggest that PTEN deleted tumors expressing low levels of AR may represent a worse prognostic subset of PCa establishing a challenge for therapeutic management. PMID:23171135

Identification of genetic risk associated with prostate cancer using ancestry informative markers

PubMed Central

Ricks-Santi, LJ; Apprey, V; Mason, T; Wilson, B; Abbas, M; Hernandez, W; Hooker, S; Doura, M; Bonney, G; Dunston, G; Kittles, R; Ahaghotu, C

2014-01-01

BACKGROUND Prostate cancer (PCa) is a common malignancy and a leading cause of cancer death among men in the United States with African-American (AA) men having the highest incidence and mortality rates. Given recent results from admixture mapping and genome-wide association studies for PCa in AA men, it is clear that many risk alleles are enriched in men with West African genetic ancestry. METHODS A total of 77 ancestry informative markers (AIMs) within surrounding candidate gene regions were genotyped and haplotyped using Pyrosequencing in 358 unrelated men enrolled in a PCa genetic association study at the Howard University Hospital between 2000 and 2004. Sequence analysis of promoter region single-nucleotide polymorphisms (SNPs) to evaluate disruption of transcription factor-binding sites was conducted using in silico methods. RESULTS Eight AIMs were significantly associated with PCa risk after adjusting for age and West African ancestry. SNP rs1993973 (intervening sequences) had the strongest association with PCa using the log-additive genetic model (P = 0.002). SNPs rs1561131 (genotypic, P = 0.007), rs1963562 (dominant, P = 0.01) and rs615382 (recessive, P = 0.009) remained highly significant after adjusting for both age and ancestry. We also tested the independent effect of each significantly associated SNP and rs1561131 (P = 0.04) and rs1963562 (P = 0.04) remained significantly associated with PCa development. After multiple comparisons testing using the false discovery rate, rs1993973 remained significant. Analysis of the rs156113–, rs1963562–rs615382l and rs1993973–rs585224 haplotypes revealed that the least frequently found haplotypes in this population were significantly associated with a decreased risk of PCa (P = 0.032 and 0.0017, respectively). CONCLUSIONS The approach for SNP selection utilized herein showed that AIMs may not only leverage increased linkage disequilibrium in populations to identify risk and protective alleles, but may also be informative in dissecting the biology of PCa and other health disparities. PMID:22801071

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bednarz, Natalia; Eltze, Elke; Semjonow, Axel

A recent study concluded that serum prostate specific antigen (PSA)-based screening is beneficial for reducing the lethality of PCa, but was also associated with a high risk of 'overdiagnosis'. Nevertheless, also PCa patients who suffered from organ confined tumors and had negative bone scans succumb to distant metastases after complete tumor resection. It is reasonable to assume that those tumors spread to other organs long before the overt manifestation of metastases. Our current results confirm that prostate tumors are highly heterogeneous. Even a small subpopulation of cells bearing BRCA1 losses can initiate PCa cell regional and distant dissemination indicating thosemore » patients which might be at high risk of metastasis. A preliminary study performed on a small cohort of multifocal prostate cancer (PCa) detected BRCA1 allelic imbalances (AI) among circulating tumor cells (CTCs). The present analysis was aimed to elucidate the biological and clinical role of BRCA1 losses on metastatic spread and tumor progression in prostate cancer patients. Experimental Design: To map molecular progression in PCa outgrowth we used FISH analysis of tissue microarrays (TMA), lymph node sections and CTC from peripheral blood. We found that 14% of 133 tested patients carried monoallelic BRCA1 loss in at least one tumor focus. Extended molecular analysis of chr17q revealed that this aberration was often a part of larger cytogenetic rearrangement involving chr17q21 accompanied by AI of the tumor suppressor gene PTEN and lack of the BRCA1 promoter methylation. The BRCA1 losses correlated with advanced T stage (p < 0.05), invasion to pelvic lymph nodes (LN, p < 0.05) as well as BR (p < 0.01). Their prevalence was twice as high within 62 LN metastases (LNMs) as in primary tumors (27%, p < 0.01). The analysis of 11 matched primary PCa-LNM pairs confirmed the suspected transmission of genetic abnormalities between those two sites. In 4 of 7 patients with metastatic disease, BRCA1 losses appeared in a minute fraction of cytokeratin- and vimentin-positive CTCs. Small subpopulations of PCa cells bearing BRCA1 losses might be one confounding factor initiating tumor dissemination and might provide an early indicator of shortened disease-free survival.« less

A Principal Components Analysis and Validation of the Coping with the College Environment Scale (CWCES)

ERIC Educational Resources Information Center

Ackermann, Margot Elise; Morrow, Jennifer Ann

2008-01-01

The present study describes the development and initial validation of the Coping with the College Environment Scale (CWCES). Participants included 433 college students who took an online survey. Principal Components Analysis (PCA) revealed six coping strategies: planning and self-management, seeking support from institutional resources, escaping…

Exosomes confer pro-survival signals to alter the phenotype of prostate cells in their surrounding environment

PubMed Central

Hosseini-Beheshti, Elham; Choi, Wendy; Weiswald, Louis-Bastien; Kharmate, Geetanjali; Ghaffari, Mazyar; Roshan-Moniri, Mani; Hassona, Mohamed D.; Chan, Leslie; Chin, Mei Yieng; Tai, Isabella T.; Rennie, Paul S.; Fazli, Ladan; Guns, Emma S. Tomlinson

2016-01-01

Prostate cancer (PCa) is the most frequently diagnosed cancer in men. Current research on tumour-related extracellular vesicles (EVs) suggests that exosomes play a significant role in paracrine signaling pathways, thus potentially influencing cancer progression via multiple mechanisms. In fact, during the last decade numerous studies have revealed the role of EVs in the progression of various pathological conditions including cancer. Moreover, differences in the proteomic, lipidomic, and cholesterol content of exosomes derived from PCa cell lines versus benign prostate cell lines confirm that exosomes could be excellent biomarker candidates. As such, as part of an extensive proteomic analysis using LCMS we previously described a potential role of exosomes as biomarkers for PCa. Current evidence suggests that uptake of EV's into the local tumour microenvironment encouraging us to further examine the role of these vesicles in distinct mechanisms involved in the progression of PCa and castration resistant PCa. For the purpose of this study, we hypothesized that exosomes play a pivotal role in cell-cell communication in the local tumour microenvironment, conferring activation of numerous survival mechanisms during PCa progression and development of therapeutic resistance. Our in vitro results demonstrate that PCa derived exosomes significantly reduce apoptosis, increase cancer cell proliferation and induce cell migration in LNCaP and RWPE-1 cells. In conjunction with our in vitro findings, we have also demonstrated that exosomes increased tumor volume and serum PSA levels in vivo when xenograft bearing mice were administered DU145 cell derived exosomes intravenously. This research suggests that, regardless of androgen receptor phenotype, exosomes derived from PCa cells significantly enhance multiple mechanisms that contribute to PCa progression. PMID:26840259

Inhibition of prostate cancer osteoblastic progression with VEGF121/rGel, a single agent targeting osteoblasts, osteoclasts, and tumor neovasculature.

PubMed

Mohamedali, Khalid A; Li, Zhi Gang; Starbuck, Michael W; Wan, Xinhai; Yang, Jun; Kim, Sehoon; Zhang, Wendy; Rosenblum, Michael G; Navone, Nora M

2011-04-15

A hallmark of prostate cancer (PCa) progression is the development of osteoblastic bone metastases, which respond poorly to available therapies. We previously reported that VEGF(121)/rGel targets osteoclast precursors and tumor neovasculature. Here we tested the hypothesis that targeting nontumor cells expressing these receptors can inhibit tumor progression in a clinically relevant model of osteoblastic PCa. Cells from MDA PCa 118b, a PCa xenograft obtained from a bone metastasis in a patient with castrate-resistant PCa, were injected into the femurs of mice. Osteoblastic progression was monitored following systemic administration of VEGF(121)/rGel. VEGF(121)/rGel was cytotoxic in vitro to osteoblast precursor cells. This cytotoxicity was specific as VEGF(121)/rGel internalization into osteoblasts was VEGF(121) receptor driven. Furthermore, VEGF(121)/rGel significantly inhibited PCa-induced bone formation in a mouse calvaria culture assay. In vivo, VEGF(121)/rGel significantly inhibited the osteoblastic progression of PCa cells in the femurs of nude mice. Microcomputed tomographic analysis revealed that VEGF(121)/rGel restored the bone volume fraction of tumor-bearing femurs to values similar to those of the contralateral (non-tumor-bearing) femurs. VEGF(121)/rGel significantly reduced the number of tumor-associated osteoclasts but did not change the numbers of peritumoral osteoblasts. Importantly, VEGF(121)/rGel-treated mice had significantly less tumor burden than control mice. Our results thus indicate that VEGF(121)/rGel inhibits osteoblastic tumor progression by targeting angiogenesis, osteoclastogenesis, and bone formation. Targeting VEGF receptor (VEGFR)-1- or VEGFR-2-expressing cells is effective in controlling the osteoblastic progression of PCa in bone. These findings provide the basis for an effective multitargeted approach for metastatic PCa. ©2011 AACR.

Small molecule screening reveals a transcription-independent pro-survival function of androgen receptor in castration-resistant prostate cancer

PubMed Central

Narizhneva, Natalia V.; Tararova, Natalia D.; Ryabokon, Petro; Shyshynova, Inna; Prokvolit, Anatoly; Komarov, Pavel G.; Purmal, Andrei A.; Gudkov, Andrei V.; Gurova, Katerina V.

2010-01-01

In prostate cancer (PCa) patients, initial responsiveness to androgen deprivation therapy is frequently followed by relapse due to development of treatment-resistant androgen-independent PCa. This is typically associated with acquisition of mutations in AR that allow activity as a transcription factor in the absence of ligand, indicating that androgen-independent PCa remains dependent on AR function. Our strategy to effectively target AR in androgen-independent PCa involved using a cell-based readout to isolate small molecules that inhibit AR transactivation function through mechanisms other than modulation of ligand binding. A number of the identified inhibitors were toxic to AR-expressing PCa cells regardless of their androgen dependence. Among these, some only suppressed PCa cell growth (ARTIS), while others induced cell death (ARTIK). ARTIK, but not ARTIS, compounds caused disappearance of AR protein from treated cells. siRNA against AR behaved like ARTIK compounds, while a dominant negative AR mutant that prevents AR-mediated transactivation but does not eliminate the protein showed only a growth suppressive effect. These observations reveal a transcription-independent function of AR that is essential for PCa cell viability and, therefore, is an ideal target for anti-PCa treatment. Indeed, several of the identified AR inhibitors demonstrated in vivo efficacy in mouse models of PCa and are candidates for pharmacologic optimization. PMID:19946220

Identification of the epigenetic reader CBX2 as a potential drug target in advanced prostate cancer.

PubMed

Clermont, Pier-Luc; Crea, Francesco; Chiang, Yan Ting; Lin, Dong; Zhang, Amy; Wang, James Z L; Parolia, Abhijit; Wu, Rebecca; Xue, Hui; Wang, Yuwei; Ding, Jiarui; Thu, Kelsie L; Lam, Wan L; Shah, Sohrab P; Collins, Colin C; Wang, Yuzhuo; Helgason, Cheryl D

2016-01-01

While localized prostate cancer (PCa) can be effectively cured, metastatic disease inevitably progresses to a lethal state called castration-resistant prostate cancer (CRPC). Emerging evidence suggests that aberrant epigenetic repression by the polycomb group (PcG) complexes fuels PCa progression, providing novel therapeutic opportunities. In the search for potential epigenetic drivers of CRPC, we analyzed the molecular profile of PcG members in patient-derived xenografts and clinical samples. Overall, our results identify the PcG protein and methyl-lysine reader CBX2 as a potential therapeutic target in advanced PCa. We report that CBX2 was recurrently up-regulated in metastatic CRPC and that elevated CBX2 expression was correlated with poor clinical outcome in PCa cohorts. Furthermore, CBX2 depletion abrogated cell viability and induced caspase 3-mediated apoptosis in metastatic PCa cell lines. Mechanistically explaining this phenotype, microarray analysis in CBX2-depleted cells revealed that CBX2 controls the expression of many key regulators of cell proliferation and metastasis. Taken together, this study provides the first evidence that CBX2 inhibition induces cancer cell death, positioning CBX2 as an attractive drug target in lethal CRPC.

Basic visual function and cortical thickness patterns in posterior cortical atrophy.

PubMed

Lehmann, Manja; Barnes, Josephine; Ridgway, Gerard R; Wattam-Bell, John; Warrington, Elizabeth K; Fox, Nick C; Crutch, Sebastian J

2011-09-01

Posterior cortical atrophy (PCA) is characterized by a progressive decline in higher-visual object and space processing, but the extent to which these deficits are underpinned by basic visual impairments is unknown. This study aimed to assess basic and higher-order visual deficits in 21 PCA patients. Basic visual skills including form detection and discrimination, color discrimination, motion coherence, and point localization were measured, and associations and dissociations between specific basic visual functions and measures of higher-order object and space perception were identified. All participants showed impairment in at least one aspect of basic visual processing. However, a number of dissociations between basic visual skills indicated a heterogeneous pattern of visual impairment among the PCA patients. Furthermore, basic visual impairments were associated with particular higher-order object and space perception deficits, but not with nonvisual parietal tasks, suggesting the specific involvement of visual networks in PCA. Cortical thickness analysis revealed trends toward lower cortical thickness in occipitotemporal (ventral) and occipitoparietal (dorsal) regions in patients with visuoperceptual and visuospatial deficits, respectively. However, there was also a lot of overlap in their patterns of cortical thinning. These findings suggest that different presentations of PCA represent points in a continuum of phenotypical variation.

Exosomes Secreted under Hypoxia Enhance Invasiveness and Stemness of Prostate Cancer Cells by Targeting Adherens Junction Molecules

PubMed Central

Ramteke, Anand; Ting, Harold; Agarwal, Chapla; Mateen, Samiha; Somasagara, Ranganathan; Hussain, Anowar; Graner, Michael; Frederick, Barbara; Agarwal, Rajesh; Deep, Gagan

2015-01-01

Hypoxic conditions in prostate cancer (PCA) are associated with poor prognosis; however, precise mechanism/s through which hypoxia promotes malignant phenotype remains unclear. Here, we analyzed the role of exosomes from hypoxic PCA cells in enhancing the invasiveness and stemness of naïve PCA cells, as well as in promoting cancer-associated fibroblast (CAF) phenotype in prostate stromal cells (PrSC). Human PCA LNCaP and PC3 cells were exposed to hypoxic (1% O2) or normoxic (21% O2) conditions, and exosomes secreted under hypoxic (ExoHypoxic) and normoxic (ExoNormoxic) conditions were isolated from conditioned media. Nanoparticle tracking analysis revealed that ExoHypoxic have smaller average size as compared to ExoNormoxic. Immunoblotting results showed a higher level of tetraspanins (CD63 and CD81), heat shock proteins (HSP90 and HSP70) and Annexin II in ExoHypoxic compared to ExoNormoxic. Co-culturing with ExoHypoxic increased the invasiveness and motility of naïve LNCaP and PC3 cells, respectively. ExoHypoxic also promoted prostasphere formation by both LNCaP and PC3 cells, and enhanced α-SMA (a CAF biomarker) expression in PrSC. Compared to ExoNormoxic, ExoHypoxic showed higher metalloproteinases activity and increased level of diverse signaling molecules (TGF-β2, TNF1α, IL6, TSG101, Akt, ILK1, and β-catenin). Furthermore, proteome analysis revealed a higher number of proteins in ExoHypoxic (160 proteins) compared to ExoNormoxic (62 proteins), primarily associated with the remodeling of epithelial adherens junction pathway. Importantly, ExoHypoxic targeted the expression of adherens junction proteins in naïve PC3 cells. These findings suggest that ExoHypoxic are loaded with unique proteins that could enhance invasiveness, stemness and induce microenvironment changes; thereby, promoting PCA aggressiveness. PMID:24347249

L-dopa decarboxylase (DDC) gene expression is related to outcome in patients with prostate cancer.

PubMed

Koutalellis, Georgios; Stravodimos, Konstantinos; Avgeris, Margaritis; Mavridis, Konstantinos; Scorilas, Andreas; Lazaris, Andreas; Constantinides, Constantinos

2012-09-01

What's known on the subject? and What does the study add? L-dopa decarboxylase (DDC) has been documented as a novel co-activator of androgen receptor transcriptional activity. Recently, it was shown that DDC gene expression is significantly higher in patients with PCa than in those with BPH. In the present study, there was a significant association between the DDC gene expression levels and the pathological stage and Gleason score of patients with prostate cancer (PCa). Moreover, DDC expression was shown to be an unfavourable prognostic marker of biochemical recurrence and disease-free survival in patients with PCa treated by radical prostatectomy. To determine whether L-dopa decarboxylase gene (DDC) expression levels in patients with prostate cancer (PCa) correlate to biochemical recurrence and disease prognosis after radical prostatectomy (RP). The present study consisted of 56 samples with confirmed malignancy from patients with PCa who had undergone RP at a single tertiary academic centre. Total RNA was isolated from tissue specimens and a SYBR Green fluorescence-based quantitative real-time polymerase chain reaction methodology was developed for the determination of DDC mRNA expression levels of the tested tissues. Follow-up time ranged between 1.0 and 62.0 months (mean ± SE, 28.6 ± 2.1 month; median, 31.5 months). Time to biochemical recurrence was defined as the interval between the surgery and the measurement of two consecutive values of prostate-specific antigen (PSA) ≥0.2 ng/mL. DDC expression levels were found to be positively correlated with the tumour-node-metastasis stage (P = 0.021) and Gleason score (P = 0.036) of the patients with PCa. Patients with PCa with raised DDC expression levels run a significantly higher risk of biochemical recurrence after RP, as indicated by Cox proportional regression analysis (P = 0.021). Multivariate Cox proportional regression models revealed the preoperative PSA-, age- and digital rectal examination-independent prognostic value of DDC expression for the prediction of disease-free survival (DFS) among patients with PCa (P = 0.036). Kaplan-Meier survival analysis confirms the significantly shorter DFS after RP of PCa with higher DDC expression levels (P = 0.015). This is the first study indicating the potential of DDC expression as a novel prognostic biomarker in patients with PCa who have undergone RP. For further evaluation and clinical application of the findings of the present study, a direct analysis of mRNA and/or its protein expression level in preoperative biopsy, blood serum and urine should be conducted. © 2012 BJU INTERNATIONAL.

Analysis of laterality and percentage of tumor involvement in 1386 prostatectomized specimens for selection of unilateral focal cryotherapy.

PubMed

Mouraviev, Vladimir; Mayes, Janice M; Madden, John F; Sun, Leon; Polascik, Thomas J

2007-04-01

In total, 1386 paraffin embedded radical prostatectomy specimens from patients with clinically localized prostate cancer (PCa) excised between 2002-06 were analyzed. Pathologic assessment paid particular attention to laterality and percentage of tumor involvement (PTI) along with pathologic Gleason Score (pGS). Completely unilateral cancers were identified in 254 (18.3%) patients, and in 39% cases of them the signs of clinically significant PCa were revealed. The majority of unilateral tumors (72%) were low volume with a PTI of < or =5. This study suggests that only a select group of men diagnosed with PCa have completely unilateral cancers that would be amenable to focal ablation therapy targeting 1 lobe. Further study is needed to develop predictive models for those patients likely to have small, unilateral cancers that may be amenable to focal therapy.

On a PCA-based lung motion model

PubMed Central

Li, Ruijiang; Lewis, John H; Jia, Xun; Zhao, Tianyu; Liu, Weifeng; Wuenschel, Sara; Lamb, James; Yang, Deshan; Low, Daniel A; Jiang, Steve B

2014-01-01

Respiration-induced organ motion is one of the major uncertainties in lung cancer radiotherapy and is crucial to be able to accurately model the lung motion. Most work so far has focused on the study of the motion of a single point (usually the tumor center of mass), and much less work has been done to model the motion of the entire lung. Inspired by the work of Zhang et al (2007 Med. Phys. 34 4772–81), we believe that the spatiotemporal relationship of the entire lung motion can be accurately modeled based on principle component analysis (PCA) and then a sparse subset of the entire lung, such as an implanted marker, can be used to drive the motion of the entire lung (including the tumor). The goal of this work is twofold. First, we aim to understand the underlying reason why PCA is effective for modeling lung motion and find the optimal number of PCA coefficients for accurate lung motion modeling. We attempt to address the above important problems both in a theoretical framework and in the context of real clinical data. Second, we propose a new method to derive the entire lung motion using a single internal marker based on the PCA model. The main results of this work are as follows. We derived an important property which reveals the implicit regularization imposed by the PCA model. We then studied the model using two mathematical respiratory phantoms and 11 clinical 4DCT scans for eight lung cancer patients. For the mathematical phantoms with cosine and an even power (2n) of cosine motion, we proved that 2 and 2n PCA coefficients and eigenvectors will completely represent the lung motion, respectively. Moreover, for the cosine phantom, we derived the equivalence conditions for the PCA motion model and the physiological 5D lung motion model (Low et al 2005 Int. J. Radiat. Oncol. Biol. Phys. 63 921–9). For the clinical 4DCT data, we demonstrated the modeling power and generalization performance of the PCA model. The average 3D modeling error using PCA was within 1 mm (0.7 ± 0.1 mm). When a single artificial internal marker was used to derive the lung motion, the average 3D error was found to be within 2 mm (1.8 ± 0.3 mm) through comprehensive statistical analysis. The optimal number of PCA coefficients needs to be determined on a patient-by-patient basis and two PCA coefficients seem to be sufficient for accurate modeling of the lung motion for most patients. In conclusion, we have presented thorough theoretical analysis and clinical validation of the PCA lung motion model. The feasibility of deriving the entire lung motion using a single marker has also been demonstrated on clinical data using a simulation approach. PMID:21865624

Application of metabonomics on an experimental model of fibrosis and cirrhosis induced by thioacetamide in rats

DOE Office of Scientific and Technical Information (OSTI.GOV)

Constantinou, Maria A.; Department of Forensic Medicine and Toxicology, Medical School, University of Athens, 75, Mikras Asias str., 11527 Athens; Theocharis, Stamatios E.

2007-01-01

Metabonomics has already been used to discriminate different pathological states in biological fields. The metabolic profiles of chronic experimental fibrosis and cirrhosis induction in rats were investigated using {sup 1}H NMR spectroscopy of liver extracts and serum combined with pattern recognition techniques. Rats were continuously administered with thioacetamide (TAA) in the drinking water (300 mg TAA/L), and sacrificed on 1st, 2nd, and 3rd month of treatment. {sup 1}H NMR spectra of aqueous and lipid liver extracts, together with serum were subjected to Principal Component Analysis (PCA). Liver portions were also subjected to histopathological examination and biochemical determination of malondialdehyde (MDA).more » Liver fibrosis and cirrhosis were progressively induced in TAA-treated rats, verified by the histopathological examination and the alterations of MDA levels. TAA administration revealed a number of changes in the {sup 1}H NMR spectra compared to control samples. The performance of PCA in liver extracts and serum, discriminated the control samples from the fibrotic and cirrhotic ones. Metabolic alterations revealed in NMR spectra during experimental liver fibrosis and cirrhosis induction, characterize the stage of fibrosis and could be illustrated by subsequent PCA of the spectra. Additionally, the PCA plots of the serum samples presented marked clustering during fibrosis progression and could be extended in clinical diagnosis for the management of cirrhotic patients.« less

Nonlinear multivariate and time series analysis by neural network methods

NASA Astrophysics Data System (ADS)

Hsieh, William W.

2004-03-01

Methods in multivariate statistical analysis are essential for working with large amounts of geophysical data, data from observational arrays, from satellites, or from numerical model output. In classical multivariate statistical analysis, there is a hierarchy of methods, starting with linear regression at the base, followed by principal component analysis (PCA) and finally canonical correlation analysis (CCA). A multivariate time series method, the singular spectrum analysis (SSA), has been a fruitful extension of the PCA technique. The common drawback of these classical methods is that only linear structures can be correctly extracted from the data. Since the late 1980s, neural network methods have become popular for performing nonlinear regression and classification. More recently, neural network methods have been extended to perform nonlinear PCA (NLPCA), nonlinear CCA (NLCCA), and nonlinear SSA (NLSSA). This paper presents a unified view of the NLPCA, NLCCA, and NLSSA techniques and their applications to various data sets of the atmosphere and the ocean (especially for the El Niño-Southern Oscillation and the stratospheric quasi-biennial oscillation). These data sets reveal that the linear methods are often too simplistic to describe real-world systems, with a tendency to scatter a single oscillatory phenomenon into numerous unphysical modes or higher harmonics, which can be largely alleviated in the new nonlinear paradigm.

Combining ANOVA-PCA with POCHEMON to analyse micro-organism development in a polymicrobial environment.

PubMed

Geurts, Brigitte P; Neerincx, Anne H; Bertrand, Samuel; Leemans, Manja A A P; Postma, Geert J; Wolfender, Jean-Luc; Cristescu, Simona M; Buydens, Lutgarde M C; Jansen, Jeroen J

2017-04-22

Revealing the biochemistry associated to micro-organismal interspecies interactions is highly relevant for many purposes. Each pathogen has a characteristic metabolic fingerprint that allows identification based on their unique multivariate biochemistry. When pathogen species come into mutual contact, their co-culture will display a chemistry that may be attributed both to mixing of the characteristic chemistries of the mono-cultures and to competition between the pathogens. Therefore, investigating pathogen development in a polymicrobial environment requires dedicated chemometric methods to untangle and focus upon these sources of variation. The multivariate data analysis method Projected Orthogonalised Chemical Encounter Monitoring (POCHEMON) is dedicated to highlight metabolites characteristic for the interaction of two micro-organisms in co-culture. However, this approach is currently limited to a single time-point, while development of polymicrobial interactions may be highly dynamic. A well-known multivariate implementation of Analysis of Variance (ANOVA) uses Principal Component Analysis (ANOVA-PCA). This allows the overall dynamics to be separated from the pathogen-specific chemistry to analyse the contributions of both aspects separately. For this reason, we propose to integrate ANOVA-PCA with the POCHEMON approach to disentangle the pathogen dynamics and the specific biochemistry in interspecies interactions. Two complementary case studies show great potential for both liquid and gas chromatography - mass spectrometry to reveal novel information on chemistry specific to interspecies interaction during pathogen development. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Reaction Kinetics for the Biocatalytic Conversion of Phenazine-1-Carboxylic Acid to 2-Hydroxyphenazine

PubMed Central

Chen, Mingmin; Cao, Hongxia; Peng, Huasong; Hu, Hongbo; Wang, Wei; Zhang, Xuehong

2014-01-01

The phenazine derivative 2-hydroxyphenazine (2-OH-PHZ) plays an important role in the biocontrol of plant diseases, and exhibits stronger bacteriostatic and fungistatic activity than phenazine-1-carboxylic acid (PCA) toward some pathogens. PhzO has been shown to be responsible for the conversion of PCA to 2-OH-PHZ, however the kinetics of the reaction have not been systematically studied. Further, the yield of 2-OH-PHZ in fermentation culture is quite low and enhancement in our understanding of the reaction kinetics may contribute to improvements in large-scale, high-yield production of 2-OH-PHZ for biological control and other applications. In this study we confirmed previous reports that free PCA is converted to 2-hydroxy-phenazine-1-carboxylic acid (2-OH-PCA) by the action of a single enzyme PhzO, and particularly demonstrate that this reaction is dependent on NADP(H) and Fe3+. Fe3+ enhanced the conversion from PCA to 2-OH-PHZ and 28°C was a optimum temperature for the conversion. However, PCA added in excess to the culture inhibited the production of 2-OH-PHZ. 2-OH-PCA was extracted and purified from the broth, and it was confirmed that the decarboxylation of 2-OH-PCA could occur without the involvement of any enzyme. A kinetic analysis of the conversion of 2-OH-PCA to 2-OH-PHZ in the absence of enzyme and under different temperatures and pHs in vitro, revealed that the conversion followed first-order reaction kinetics. In the fermentation, the concentration of 2-OH-PCA increased to about 90 mg/L within a red precipitate fraction, as compared to 37 mg/L within the supernatant. The results of this study elucidate the reaction kinetics involved in the biosynthesis of 2-OH-PHZ and provide insights into in vitro methods to enhance yields of 2-OH-PHZ. PMID:24905009

Ripening-dependent metabolic changes in the volatiles of pineapple (Ananas comosus (L.) Merr.) fruit: II. Multivariate statistical profiling of pineapple aroma compounds based on comprehensive two-dimensional gas chromatography-mass spectrometry.

PubMed

Steingass, Christof Björn; Jutzi, Manfred; Müller, Jenny; Carle, Reinhold; Schmarr, Hans-Georg

2015-03-01

Ripening-dependent changes of pineapple volatiles were studied in a nontargeted profiling analysis. Volatiles were isolated via headspace solid phase microextraction and analyzed by comprehensive 2D gas chromatography and mass spectrometry (HS-SPME-GC×GC-qMS). Profile patterns presented in the contour plots were evaluated applying image processing techniques and subsequent multivariate statistical data analysis. Statistical methods comprised unsupervised hierarchical cluster analysis (HCA) and principal component analysis (PCA) to classify the samples. Supervised partial least squares discriminant analysis (PLS-DA) and partial least squares (PLS) regression were applied to discriminate different ripening stages and describe the development of volatiles during postharvest storage, respectively. Hereby, substantial chemical markers allowing for class separation were revealed. The workflow permitted the rapid distinction between premature green-ripe pineapples and postharvest-ripened sea-freighted fruits. Volatile profiles of fully ripe air-freighted pineapples were similar to those of green-ripe fruits postharvest ripened for 6 days after simulated sea freight export, after PCA with only two principal components. However, PCA considering also the third principal component allowed differentiation between air-freighted fruits and the four progressing postharvest maturity stages of sea-freighted pineapples.

Gene expression profile of mouse prostate tumors reveals dysregulations in major biological processes and identifies potential murine targets for preclinical development of human prostate cancer therapy.

PubMed

Haram, Kerstyn M; Peltier, Heidi J; Lu, Bin; Bhasin, Manoj; Otu, Hasan H; Choy, Bob; Regan, Meredith; Libermann, Towia A; Latham, Gary J; Sanda, Martin G; Arredouani, Mohamed S

2008-10-01

Translation of preclinical studies into effective human cancer therapy is hampered by the lack of defined molecular expression patterns in mouse models that correspond to the human counterpart. We sought to generate an open source TRAMP mouse microarray dataset and to use this array to identify differentially expressed genes from human prostate cancer (PCa) that have concordant expression in TRAMP tumors, and thereby represent lead targets for preclinical therapy development. We performed microarrays on total RNA extracted and amplified from eight TRAMP tumors and nine normal prostates. A subset of differentially expressed genes was validated by QRT-PCR. Differentially expressed TRAMP genes were analyzed for concordant expression in publicly available human prostate array datasets and a subset of resulting genes was analyzed by QRT-PCR. Cross-referencing differentially expressed TRAMP genes to public human prostate array datasets revealed 66 genes with concordant expression in mouse and human PCa; 56 between metastases and normal and 10 between primary tumor and normal tissues. Of these 10 genes, two, Sox4 and Tubb2a, were validated by QRT-PCR. Our analysis also revealed various dysregulations in major biologic pathways in the TRAMP prostates. We report a TRAMP microarray dataset of which a gene subset was validated by QRT-PCR with expression patterns consistent with previous gene-specific TRAMP studies. Concordance analysis between TRAMP and human PCa associated genes supports the utility of the model and suggests several novel molecular targets for preclinical therapy.

Principal component and normal mode analysis of proteins; a quantitative comparison using the GroEL subunit.

PubMed

Skjaerven, Lars; Martinez, Aurora; Reuter, Nathalie

2011-01-01

Principal component analysis (PCA) and normal mode analysis (NMA) have emerged as two invaluable tools for studying conformational changes in proteins. To compare these approaches for studying protein dynamics, we have used a subunit of the GroEL chaperone, whose dynamics is well characterized. We first show that both PCA on trajectories from molecular dynamics (MD) simulations and NMA reveal a general dynamical behavior in agreement with what has previously been described for GroEL. We thus compare the reproducibility of PCA on independent MD runs and subsequently investigate the influence of the length of the MD simulations. We show that there is a relatively poor one-to-one correspondence between eigenvectors obtained from two independent runs and conclude that caution should be taken when analyzing principal components individually. We also observe that increasing the simulation length does not improve the agreement with the experimental structural difference. In fact, relatively short MD simulations are sufficient for this purpose. We observe a rapid convergence of the eigenvectors (after ca. 6 ns). Although there is not always a clear one-to-one correspondence, there is a qualitatively good agreement between the movements described by the first five modes obtained with the three different approaches; PCA, all-atoms NMA, and coarse-grained NMA. It is particularly interesting to relate this to the computational cost of the three methods. The results we obtain on the GroEL subunit contribute to the generalization of robust and reproducible strategies for the study of protein dynamics, using either NMA or PCA of trajectories from MD simulations. © 2010 Wiley-Liss, Inc.

Age-related differences in early novelty processing: Using PCA to parse the overlapping anterior P2 and N2 components

PubMed Central

Daffner, Kirk R.; Alperin, Brittany R.; Mott, Katherine K.; Tusch, Erich; Holcomb, Phillip J.

2015-01-01

Previous work demonstrated age-associated increases in the anterior P2 and age-related decreases in the anterior N2 in response to novel stimuli. Principal component analysis (PCA) was used to determine if the inverse relationship between these components was due to their temporal and spatial overlap. PCA revealed an early anterior P2, sensitive to task relevance, and a late anterior P2, responsive to novelty, both exhibiting age-related amplitude increases. A PCA factor representing the anterior N2, sensitive to novelty, exhibited age-related amplitude decreases. The late P2 and N2 to novels inversely correlated. Larger late P2 amplitude to novels was associated with better behavioral performance. Age-related differences in the anterior P2 and N2 to novel stimuli likely represent age-associated changes in independent cognitive operations. Enhanced anterior P2 activity (indexing augmentation in motivational salience) may be a compensatory mechanism for diminished anterior N2 activity (indexing reduced ability of older adults to process ambiguous representations). PMID:25596483

Analysis and Evaluation of the Characteristic Taste Components in Portobello Mushroom.

PubMed

Wang, Jinbin; Li, Wen; Li, Zhengpeng; Wu, Wenhui; Tang, Xueming

2018-05-10

To identify the characteristic taste components of the common cultivated mushroom (brown; Portobello), Agaricus bisporus, taste components in the stipe and pileus of Portobello mushroom harvested at different growth stages were extracted and identified, and principal component analysis (PCA) and taste active value (TAV) were used to reveal the characteristic taste components during the each of the growth stages of Portobello mushroom. In the stipe and pileus, 20 and 14 different principal taste components were identified, respectively, and they were considered as the principal taste components of Portobello mushroom fruit bodies, which included most amino acids and 5'-nucleotides. Some taste components that were found at high levels, such as lactic acid and citric acid, were not detected as Portobello mushroom principal taste components through PCA. However, due to their high content, Portobello mushroom could be used as a source of organic acids. The PCA and TAV results revealed that 5'-GMP, glutamic acid, malic acid, alanine, proline, leucine, and aspartic acid were the characteristic taste components of Portobello mushroom fruit bodies. Portobello mushroom was also found to be rich in protein and amino acids, so it might also be useful in the formulation of nutraceuticals and functional food. The results in this article could provide a theoretical basis for understanding and regulating the characteristic flavor components synthesis process of Portobello mushroom. © 2018 Institute of Food Technologists®.

ARLTS1 and Prostate Cancer Risk - Analysis of Expression and Regulation

PubMed Central

Siltanen, Sanna; Fischer, Daniel; Rantapero, Tommi; Laitinen, Virpi; Mpindi, John Patrick; Kallioniemi, Olli; Wahlfors, Tiina; Schleutker, Johanna

2013-01-01

Prostate cancer (PCa) is a heterogeneous trait for which several susceptibility loci have been implicated by genome-wide linkage and association studies. The genomic region 13q14 is frequently deleted in tumour tissues of both sporadic and familial PCa patients and is consequently recognised as a possible locus of tumour suppressor gene(s). Deletions of this region have been found in many other cancers. Recently, we showed that homozygous carriers for the T442C variant of the ARLTS1 gene (ADP-ribosylation factor-like tumour suppressor protein 1 or ARL11, located at 13q14) are associated with an increased risk for both unselected and familial PCa. Furthermore, the variant T442C was observed in greater frequency among malignant tissue samples, PCa cell lines and xenografts, supporting its role in PCa tumourigenesis. In this study, 84 PCa cases and 15 controls were analysed for ARLTS1 expression status in blood-derived RNA. A statistically significant (p = 0.0037) decrease of ARLTS1 expression in PCa cases was detected. Regulation of ARLTS1 expression was analysed with eQTL (expression quantitative trait loci) methods. Altogether fourteen significant cis-eQTLs affecting the ARLTS1 expression level were found. In addition, epistatic interactions of ARLTS1 genomic variants with genes involved in immune system processes were predicted with the MDR program. In conclusion, this study further supports the role of ARLTS1 as a tumour suppressor gene and reveals that the expression is regulated through variants localised in regulatory regions. PMID:23940804

Discrimination of cherry wines based on their sensory properties and aromatic fingerprinting using HS-SPME-GC-MS and multivariate analysis.

PubMed

Xiao, Zuobing; Liu, Shengjiang; Gu, Yongbo; Xu, Na; Shang, Yi; Zhu, Jiancai

2014-03-01

Volatiles of cherry wines were extracted by headspace solid phase microextraction (HS-SPME) and analyzed by gas chromatography mass spectrometry (GC-MS), multivariate statistical techniques (such as principal component analysis (PCA) and cluster analysis (CA) and correlation analysis) to differentiate sensory attributes of 3 groups of the wines through characterization of volatiles of cherry wine. Seventy-five volatiles were identified in 9 samples, including 29 esters, 22 alcohols, 8 acids, 3 ketones, 5 aldehydes, and 8 miscellaneous compounds. The PCA results showed that the cherry wines were mainly differentiated by 8 sensory attributes. The samples W2, W4, and W7 were grouped around sweet aromatic and the samples W1, W5, and W9 were highly associated with the sweet, esters, green, bitter, and fermented. Nevertheless, the samples W3, W6, and W8 were located close to the sour, alcoholic, and fruity. The final result of correlation analysis was in conformity with the conclusion of PCA. The CA results showed that the group of W2, W4, and W7, and the group of W1, W5, and W9 had less difference than the group of W3, W6, and W8. The reason should be that esterification reactions and fermentation process during the ageing period was more extended. The results of analyzing revealed that HS-SPME-GC-MS coupled with chemometrics could give an appropriate way of characterizing and classifying the cherry wines. Attributes that represent and discriminate among cherry wines might be made use of a better comprehending of the wines and for being utilized in future work. In addition, several chemometrics were used to classify the type of wines and try to install the relationship between volatiles and sensory property. Especially, PCA clearly revealed that the most contributing compounds for sensory attributes of cherry wines, CA was a more applicable way to distinguish types of cherry wines. Therefore, a feasible method that would be helpful to promote the quality of the wines by improving the winemaking process and analyzing aromatic characteristics of wines. © 2014 Institute of Food Technologists®

Exploring patterns enriched in a dataset with contrastive principal component analysis.

PubMed

Abid, Abubakar; Zhang, Martin J; Bagaria, Vivek K; Zou, James

2018-05-30

Visualization and exploration of high-dimensional data is a ubiquitous challenge across disciplines. Widely used techniques such as principal component analysis (PCA) aim to identify dominant trends in one dataset. However, in many settings we have datasets collected under different conditions, e.g., a treatment and a control experiment, and we are interested in visualizing and exploring patterns that are specific to one dataset. This paper proposes a method, contrastive principal component analysis (cPCA), which identifies low-dimensional structures that are enriched in a dataset relative to comparison data. In a wide variety of experiments, we demonstrate that cPCA with a background dataset enables us to visualize dataset-specific patterns missed by PCA and other standard methods. We further provide a geometric interpretation of cPCA and strong mathematical guarantees. An implementation of cPCA is publicly available, and can be used for exploratory data analysis in many applications where PCA is currently used.

The Effect of Phenazine-1-Carboxylic Acid on Mycelial Growth of Botrytis cinerea Produced by Pseudomonas aeruginosa LV Strain.

PubMed

Simionato, Ane S; Navarro, Miguel O P; de Jesus, Maria L A; Barazetti, André R; da Silva, Caroline S; Simões, Glenda C; Balbi-Peña, Maria I; de Mello, João C P; Panagio, Luciano A; de Almeida, Ricardo S C; Andrade, Galdino; de Oliveira, Admilton G

2017-01-01

One of the most important postharvest plant pathogens that affect strawberries, grapes and tomatoes is Botrytis cinerea , known as gray mold. The fungus remains in latent form until spore germination conditions are good, making infection control difficult, causing great losses in the whole production chain. This study aimed to purify and identify phenazine-1-carboxylic acid (PCA) produced by the Pseudomonas aeruginosa LV strain and to determine its antifungal activity against B. cinerea . The compounds produced were extracted with dichloromethane and passed through a chromatographic process. The purity level of PCA was determined by reversed-phase high-performance liquid chromatography semi-preparative. The structure of PCA was confirmed by nuclear magnetic resonance and electrospray ionization mass spectrometry. Antifungal activity was determined by the dry paper disk and minimum inhibitory concentration (MIC) methods and identified by scanning electron microscopy and confocal microscopy. The results showed that PCA inhibited mycelial growth, where MIC was 25 μg mL -1 . Microscopic analysis revealed a reduction in exopolysaccharide (EPS) formation, showing distorted and damaged hyphae of B. cinerea . The results suggested that PCA has a high potential in the control of B. cinerea and inhibition of EPS (important virulence factor). This natural compound is a potential alternative to postharvest control of gray mold disease.

An inter-comparison of PM10 source apportionment using PCA and PMF receptor models in three European sites.

PubMed

Cesari, Daniela; Amato, F; Pandolfi, M; Alastuey, A; Querol, X; Contini, D

2016-08-01

Source apportionment of aerosol is an important approach to investigate aerosol formation and transformation processes as well as to assess appropriate mitigation strategies and to investigate causes of non-compliance with air quality standards (Directive 2008/50/CE). Receptor models (RMs) based on chemical composition of aerosol measured at specific sites are a useful, and widely used, tool to perform source apportionment. However, an analysis of available studies in the scientific literature reveals heterogeneities in the approaches used, in terms of "working variables" such as the number of samples in the dataset and the number of chemical species used as well as in the modeling tools used. In this work, an inter-comparison of PM10 source apportionment results obtained at three European measurement sites is presented, using two receptor models: principal component analysis coupled with multi-linear regression analysis (PCA-MLRA) and positive matrix factorization (PMF). The inter-comparison focuses on source identification, quantification of source contribution to PM10, robustness of the results, and how these are influenced by the number of chemical species available in the datasets. Results show very similar component/factor profiles identified by PCA and PMF, with some discrepancies in the number of factors. The PMF model appears to be more suitable to separate secondary sulfate and secondary nitrate with respect to PCA at least in the datasets analyzed. Further, some difficulties have been observed with PCA in separating industrial and heavy oil combustion contributions. Commonly at all sites, the crustal contributions found with PCA were larger than those found with PMF, and the secondary inorganic aerosol contributions found by PCA were lower than those found by PMF. Site-dependent differences were also observed for traffic and marine contributions. The inter-comparison of source apportionment performed on complete datasets (using the full range of available chemical species) and incomplete datasets (with reduced number of chemical species) allowed to investigate the sensitivity of source apportionment (SA) results to the working variables used in the RMs. Results show that, at both sites, the profiles and the contributions of the different sources calculated with PMF are comparable within the estimated uncertainties indicating a good stability and robustness of PMF results. In contrast, PCA outputs are more sensitive to the chemical species present in the datasets. In PCA, the crustal contributions are higher in the incomplete datasets and the traffic contributions are significantly lower for incomplete datasets.

Kinetics of Forming Aldehydes in Frying Oils and Their Distribution in French Fries Revealed by LC-MS-Based Chemometrics.

PubMed

Wang, Lei; Csallany, A Saari; Kerr, Brian J; Shurson, Gerald C; Chen, Chi

2016-05-18

In this study, the kinetics of aldehyde formation in heated frying oils was characterized by 2-hydrazinoquinoline derivatization, liquid chromatography-mass spectrometry (LC-MS) analysis, principal component analysis (PCA), and hierarchical cluster analysis (HCA). The aldehydes contributing to time-dependent separation of heated soybean oil (HSO) in a PCA model were grouped by the HCA into three clusters (A1, A2, and B) on the basis of their kinetics and fatty acid precursors. The increases of 4-hydroxynonenal (4-HNE) and the A2-to-B ratio in HSO were well-correlated with the duration of thermal stress. Chemometric and quantitative analysis of three frying oils (soybean, corn, and canola oils) and French fry extracts further supported the associations between aldehyde profiles and fatty acid precursors and also revealed that the concentrations of pentanal, hexanal, acrolein, and the A2-to-B ratio in French fry extracts were more comparable to their values in the frying oils than other unsaturated aldehydes. All of these results suggest the roles of specific aldehydes or aldehyde clusters as novel markers of the lipid oxidation status for frying oils or fried foods.

Y-chromosome phylogeographic analysis of the Greek-Cypriot population reveals elements consistent with Neolithic and Bronze Age settlements.

PubMed

Voskarides, Konstantinos; Mazières, Stéphane; Hadjipanagi, Despina; Di Cristofaro, Julie; Ignatiou, Anastasia; Stefanou, Charalambos; King, Roy J; Underhill, Peter A; Chiaroni, Jacques; Deltas, Constantinos

2016-01-01

The archeological record indicates that the permanent settlement of Cyprus began with pioneering agriculturalists circa 11,000 years before present, (ca. 11,000 y BP). Subsequent colonization events followed, some recognized regionally. Here, we assess the Y-chromosome structure of Cyprus in context to regional populations and correlate it to phases of prehistoric colonization. Analysis of haplotypes from 574 samples showed that island-wide substructure was barely significant in a spatial analysis of molecular variance (SAMOVA). However, analyses of molecular variance (AMOVA) of haplogroups using 92 binary markers genotyped in 629 Cypriots revealed that the proportion of variance among the districts was irregularly distributed. Principal component analysis (PCA) revealed potential genetic associations of Greek-Cypriots with neighbor populations. Contrasting haplogroups in the PCA were used as surrogates of parental populations. Admixture analyses suggested that the majority of G2a-P15 and R1b-M269 components were contributed by Anatolia and Levant sources, respectively, while Greece Balkans supplied the majority of E-V13 and J2a-M67. Haplotype-based expansion times were at historical levels suggestive of recent demography. Analyses of Cypriot haplogroup data are consistent with two stages of prehistoric settlement. E-V13 and E-M34 are widespread, and PCA suggests sourcing them to the Balkans and Levant/Anatolia, respectively. The persistent pre-Greek component is represented by elements of G2-U5(xL30) haplogroups: U5*, PF3147, and L293. J2b-M205 may contribute also to the pre-Greek strata. The majority of R1b-Z2105 lineages occur in both the westernmost and easternmost districts. Distinctively, sub-haplogroup R1b- M589 occurs only in the east. The absence of R1b- M589 lineages in Crete and the Balkans and the presence in Asia Minor are compatible with Late Bronze Age influences from Anatolia rather than from Mycenaean Greeks.

The role of serum neuron-specific enolase in patients with prostate cancer: a systematic review of the recent literature.

PubMed

Muoio, Barbara; Pascale, Mariarosa; Roggero, Enrico

2018-01-01

In this systematic review, we evaluated the value of serum concentrations of neuron-specific enolase (NSE) in patients with prostate cancer (PCa) in order to clarify the possible role of NSE in the diagnosis, management, treatment and monitoring of PCa. A comprehensive search of the recent literature was conducted to find relevant data on the role of NSE in PCa. Two hundred and eighty-two records were revealed, and 19 articles including 1,772 patients with PCa (either confirmed or suspected) were selected. After reviewing the articles, the major result was that elevated serum NSE appears to correlate with prognosis in advanced PCa, particularly in patients with progressive and metastatic castration-resistant PCa. Based on the existing literature, the role of serum NSE in PCa patients should be further evaluated.

Genome-wide divergence and linkage disequilibrium analyses for Capsicum baccatum revealed by genome-anchored single nucleotide polymorphisms

USDA-ARS?s Scientific Manuscript database

Principal component analysis (PCA) with 36,621 polymorphic genome-anchored single nucleotide polymorphisms (SNPs) identified collectively for Capsicum annuum and Capsicum baccatum was used to show the distribution of these 2 important incompatible cultivated pepper species. Estimated mean nucleotide...

Examining markers in 8q24 to explain differences in evidence for association with cleft lip with/without cleft palate between Asians and Europeans

PubMed Central

Murray, Tanda; Taub, Margaret A.; Ruczinski, Ingo; Scott, Alan F.; Hetmanski, Jacqueline B.; Schwender, Holger; Patel, Poorav; Zhang, Tian Xiao; Munger, Ronald G.; Wilcox, Allen J.; Ye, Xiaoqian; Wang, Hong; Wu, Tao; Wu-Chou, Yah Huei; Shi, Bing; Jee, Sun Ha; Chong, Samuel; Yeow, Vincent; Murray, Jeffrey C.; Marazita, Mary L.; Beaty, Terri H.

2013-01-01

In a recent genome wide association study (GWAS) from an international consortium, evidence of linkage and association in chr8q24 was much stronger among non-syndromic cleft lip/palate (CL/P) case-parent trios of European ancestry than among trios of Asian ancestry. We examined marker information content and haplotype diversity across 13 recruitment sites (from Europe, USA and Asia) separately, and conducted principal components analysis (PCA) on parents. As expected, PCA revealed large genetic distances between Europeans and Asians, and a north-south cline from Korea to Singapore in Asia, with Filipino parents forming a somewhat distinct Southeast Asian cluster. Hierarchical clustering of SNP heterozygosity revealed two major clades consistent with PCA results. All genotyped SNPs giving p<10−6 in the allelic TDT showed higher heterozygosity in Europeans than Asians. On average, European ancestry parents had higher haplotype diversity than Asians. Imputing additional variants across chr8q24 increased the strength of statistical evidence among Europeans and also revealed a significant signal among Asians (although it did not reach genome-wide significance). Tests for SNP-population interaction were negative, indicating the lack of strong signal for 8q24 in families of Asian ancestry was not due to any distinct genetic effect, but could simply reflect low power due to lower allele frequencies in Asians. PMID:22508319

Principal component and spatial correlation analysis of spectroscopic-imaging data in scanning probe microscopy.

PubMed

Jesse, Stephen; Kalinin, Sergei V

2009-02-25

An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.

Inhibition of prostate cancer osteoblastic progression with VEGF121/rGel, a single agent targeting osteoblasts, osteoclasts, and tumor neovasculature

PubMed Central

Mohamedali, Khalid A.; Li, Zhi Gang; Starbuck, Michael W.; Wan, Xinhai; Yang, Jun; Kim, Sehoon; Zhang, Wendy; Rosenblum, Michael G.; Navone, Nora M.

2011-01-01

Purpose A hallmark of prostate cancer (PCa) progression is the development of osteoblastic bone metastases, which respond poorly to available therapies. We previously reported that VEGF121/rGel targets osteoclast precursors and tumor neovasculature. Here we tested the hypothesis that targeting non-tumor cells expressing these receptors can inhibit tumor progression in a clinically relevant model of osteoblastic PCa. Experimental Design Cells from MDA PCa 118b, a PCa xenograft obtained from a bone metastasis in a patient with castrate-resistant PCa, were injected into the femurs of mice. Osteoblastic progression was monitored following systemic administration of VEGF121/rGel. Results VEGF121/rGel was cytotoxic in vitro to osteoblast precursor cells. This cytotoxicity was specific as VEGF121/rGel internalization into osteoblasts was VEGF121 receptor driven. Furthermore, VEGF121/rGel significantly inhibited PCa-induced bone formation in a mouse calvaria culture assay. In vivo, VEGF121/rGel significantly inhibited the osteoblastic progression of PCa cells in the femurs of nude mice. Microcomputed tomography analysis revealed that VEGF121/rGel restored the bone volume fraction of tumor-bearing femurs to values similar to those of the contralateral (non–tumor bearing) femurs. VEGF121/rGel significantly reduced the number of tumor-associated osteoclasts but did not change the numbers of peritumoral osteoblasts. Importantly, VEGF121/rGel-treated mice had significantly less tumor burden than control mice. Our results thus indicate that VEGF121/rGel inhibits osteoblastic tumor progression by targeting angiogenesis, osteoclastogenesis, and bone formation. Conclusions Targeting VEGFR-1 – or VEGFR-2–expressing cells is effective in controlling the osteoblastic progression of PCa in bone. These findings provide the basis for an effective multitargeted approach for metastatic PCa. PMID:21343372

MiR-139-5p is Increased in the Peripheral Blood of Patients with Prostate Cancer.

PubMed

Pang, Cheng; Liu, Ming; Fang, Weiwei; Guo, Jun; Zhang, Zhipeng; Wu, Pengjie; Zhang, Yaoguang; Wang, Jianye

2016-01-01

Emerging evidence suggested that microRNAs (miRNAs) play a causal role in cancer tumorigenesis. Aberrant expression of miRNA (miR)-139-5p has been observed in various types of cancers. The present study evaluated the relationship between miR-139-5p expression levels and prostate cancer (PCa), to assess the feasibility of using peripheral blood miR-139-5p as a potential non-invasive biomarker for PCa. Total RNA was extracted from peripheral whole blood samples from 45 PCa patients, 45 benign prostatic hyperplasia (BPH) patients and 50 healthy controls (HC). The expression of miR-139-5p was assessed by reverse transcription quantitative polymerase chain reaction. MiR-139-5p in peripheral blood was significantly higher in PCa patients than in patients with BPH and HC individuals (P<0.001). Higher miR-139-5p expression was observed to be associated with certain clinicopathological parameters, including PSA>20ng/ml (P<0.05), pathological tumor stage 3/4 (P<0.05) and Gleason score >7 (P<0.01). A receiver operating characteristic (ROC) curve analysis revealed that miR-139-5p distinguished PCa patients from BPH patients [area under the curve (AUC), 0.936; 95% CI, 0.878-0.993; P<0.001]. Peripheral blood miR-139-5p may be utilized as a potential novel non-invasive biomarker for PCa screening. © 2016 The Author(s) Published by S. Karger AG, Basel.

Priority of VHS Development Based in Potential Area using Principal Component Analysis

NASA Astrophysics Data System (ADS)

Meirawan, D.; Ana, A.; Saripudin, S.

2018-02-01

The current condition of VHS is still inadequate in quality, quantity and relevance. The purpose of this research is to analyse the development of VHS based on the development of regional potential by using principal component analysis (PCA) in Bandung, Indonesia. This study used descriptive qualitative data analysis using the principle of secondary data reduction component. The method used is Principal Component Analysis (PCA) analysis with Minitab Statistics Software tool. The results of this study indicate the value of the lowest requirement is a priority of the construction of development VHS with a program of majors in accordance with the development of regional potential. Based on the PCA score found that the main priority in the development of VHS in Bandung is in Saguling, which has the lowest PCA value of 416.92 in area 1, Cihampelas with the lowest PCA value in region 2 and Padalarang with the lowest PCA value.

Comprehensive analysis of commercial willow bark extracts by new technology platform: combined use of metabolomics, high-performance liquid chromatography-solid-phase extraction-nuclear magnetic resonance spectroscopy and high-resolution radical scavenging assay.

PubMed

Agnolet, Sara; Wiese, Stefanie; Verpoorte, Robert; Staerk, Dan

2012-11-02

Here, proof-of-concept of a new analytical platform used for the comprehensive analysis of a small set of commercial willow bark products is presented, and compared with a traditional standardization solely based on analysis of salicin and salicin derivatives. The platform combines principal component analysis (PCA) of two chemical fingerprints, i.e., HPLC and (1)H NMR data, and a pharmacological fingerprint, i.e., high-resolution 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonate) radical cation (ABTS(+)) reduction profile, with targeted identification of constituents of interest by hyphenated HPLC-solid-phase extraction-tube transfer NMR, i.e., HPLC-SPE-ttNMR. Score plots from PCA of HPLC and (1)H NMR fingerprints showed the same distinct grouping of preparations formulated as capsules of Salix alba bark and separation of S. alba cortex. Loading plots revealed this to be due to high amount of salicin in capsules and ampelopsin, taxifolin, 7-O-methyltaxifolin-3'-O-glucoside, and 7-O-methyltaxifolin in S. alba cortex, respectively. PCA of high-resolution radical scavenging profiles revealed clear separation of preparations along principal component 1 due to the major radical scavengers (+)-catechin and ampelopsin. The new analytical platform allowed identification of 16 compounds in commercial willow bark extracts, and identification of ampelopsin, taxifolin, 7-O-methyltaxifolin-3'-O-glucoside, and 7-O-methyltaxifolin in S. alba bark extract is reported for the first time. The detection of the novel compound, ethyl 1-hydroxy-6-oxocyclohex-2-enecarboxylate, is also described. Copyright © 2012 Elsevier B.V. All rights reserved.

Characterisation of volatile profile and sensory analysis of fresh-cut "Radicchio di Chioggia" stored in air or modified atmosphere.

PubMed

Cozzolino, Rosaria; Martignetti, Antonella; Pellicano, Mario Paolo; Stocchero, Matteo; Cefola, Maria; Pace, Bernardo; De Giulio, Beatrice

2016-02-01

The volatile profile of two hybrids of "Radicchio di Chioggia", Corelli and Botticelli, stored in air or passive modified atmosphere (MAP) during 12 days of cold storage, was monitored by solid phase micro-extraction (SPME) GC-MS. Botticelli samples were also subjected to sensory analysis. Totally, 61 volatile organic compounds (VOCs) were identified in the headspace of radicchio samples. Principal component analysis (PCA) showed that fresh product possessed a metabolic content similar to that of the MAP samples after 5 and 8 days of storage. Projection to latent structures by partial least squares (PLS) regression analysis showed the volatiles content of the samples varied depending only on the packaging conditions. Specifically, 12 metabolites describing the time evolution and explaining the effects of the different storage conditions were highlighted. Finally, a PCA analysis revealed that VOCs profile significantly correlated with sensory attributes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Noninvasive detection of nasopharyngeal carcinoma based on saliva proteins using surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Lin, Xueliang; Lin, Duo; Ge, Xiaosong; Qiu, Sufang; Feng, Shangyuan; Chen, Rong

2017-10-01

The present study evaluated the capability of saliva analysis combining membrane protein purification with surface-enhanced Raman spectroscopy (SERS) for noninvasive detection of nasopharyngeal carcinoma (NPC). A rapid and convenient protein purification method based on cellulose acetate membrane was developed. A total of 659 high-quality SERS spectra were acquired from purified proteins extracted from the saliva samples of 170 patients with pathologically confirmed NPC and 71 healthy volunteers. Spectral analysis of those saliva protein SERS spectra revealed specific changes in some biochemical compositions, which were possibly associated with NPC transformation. Furthermore, principal component analysis combined with linear discriminant analysis (PCA-LDA) was utilized to analyze and classify the saliva protein SERS spectra from NPC and healthy subjects. Diagnostic sensitivity of 70.7%, specificity of 70.3%, and diagnostic accuracy of 70.5% could be achieved by PCA-LDA for NPC identification. These results show that this assay based on saliva protein SERS analysis holds promising potential for developing a rapid, noninvasive, and convenient clinical tool for NPC screening.

1H Nuclear Magnetic Resonance Study of Olive Oils Commercially Available as Italian Products in the United States of America

PubMed Central

Del Coco, Laura; Schena, Francesco Paolo; Fanizzi, Francesco Paolo

2012-01-01

Multivariate analysis of 1H NMR data has been used for the characterization of 12 blended olive oils commercially available in the U.S. as Italian products. Chemometric methods such as unsupervised Principal Component Analysis (PCA) allowed good discrimination and gave some affinity indications for the U.S. market olive oils compared to other single cultivars of extra virgin olive oil such as Coratina and Ogliarola from Apulia, one of Italy’s leading olive oil producers, Picual (Spain), Kalamata (Greece) and Sfax (Tunisia). The olive oils commercially available as Italian products in the U.S. market clustered into 3 groups. Among them only the first (7 samples) and the second group (2 samples) showed PCA ranges similar to European references. Two oils of the third group (3 samples) were more similar to Tunisian references. In conclusion, our study revealed that most EVOO (extra virgin olive oils) tested were closer to Greek (in particular) and Spanish olive oils than Apulia EVOO. The PCA loadings disclose the components responsible for the discrimination as unsaturated (oleic, linoleic, linolenic) and saturated fatty acids. All are of great importance because of their nutritional value and differential effects on the oxidative stability of oils. It is evident that this approach has the potential to reveal the origin of EVOO, although the results support the need for a larger database, including EVOO from other Italian regions. PMID:22690321

Somatostatin Derivate (smsDX) Attenuates the TAM-Stimulated Proliferation, Migration and Invasion of Prostate Cancer via NF-κB Regulation.

PubMed

Guo, Zhaoxin; Xing, Zhaoquan; Cheng, Xiangyu; Fang, Zhiqing; Jiang, Chao; Su, Jing; Zhou, Zunlin; Xu, Zhonghua; Holmberg, Anders; Nilsson, Sten; Liu, Zhaoxu

2015-01-01

Tumor development and progression are influenced by macrophages of the surrounding microenvironment. To investigate the influences of an inflammatory tumor microenvironment on the growth and metastasis of prostate cancer, the present study used a co-culture model of prostate cancer (PCa) cells with tumor-associated macrophage (TAM)-conditioned medium (MCM). MCM promoted PCa cell (LNCaP, DU145 and PC-3) growth, and a xenograft model in nude mice consistently demonstrated that MCM could promote tumor growth. MCM also stimulated migration and invasion in vitro. Somatostatin derivate (smsDX) significantly attenuated the TAM-stimulated proliferation, migration and invasion of prostate cancer. Immunohistochemistry revealed that NF-κB was over-expressed in PCa and BPH with chronic inflammatory tissue specimens and was positively correlated with macrophage infiltration. Further investigation into the underlying mechanism revealed that NF-κB played an important role in macrophage infiltration. SmsDX inhibited the paracrine loop between TAM and PCa cells and may represent a potential therapeutic agent for PCa.

Behavior of the PCA3 gene in the urine of men with high grade prostatic intraepithelial neoplasia.

PubMed

Morote, Juan; Rigau, Marina; Garcia, Marta; Mir, Carmen; Ballesteros, Carlos; Planas, Jacques; Raventós, Carles X; Placer, José; de Torres, Inés M; Reventós, Jaume; Doll, Andreas

2010-12-01

An ideal marker for the early detection of prostate cancer (PCa) should also differentiate between men with isolated high grade prostatic intraepithelial neoplasia (HGPIN) and those with PCa. Prostate Cancer Gene 3 (PCA3) is a highly specific PCa gene and its score, in relation to the PSA gene in post-prostate massage urine (PMU-PCA3), seems to be useful in ruling out PCa, especially after a negative prostate biopsy. Because PCA3 is also expressed in the HGPIN lesion, the aim of this study was to determine the efficacy of PMU-PCA3 scores for ruling out PCa in men with previous HGPIN. The PMU-PCA3 score was assessed by quantitative PCR (multiplex research assay) in 244 men subjected to prostate biopsy: 64 men with an isolated HGPIN (no cancer detected after two or more repeated biopsies), 83 men with PCa and 97 men with benign pathology findings (BP: no PCa, HGPIN or ASAP). The median PMU-PCA3 score was 1.56 in men with BP, 2.01 in men with HGPIN (p = 0.128) and 9.06 in men with PCa (p = 0.008). The AUC in the ROC analysis was 0.705 in the subset of men with BP and PCa, while it decreased to 0.629 when only men with isolated HGPIN and PCa were included in the analysis. Fixing the sensitivity of the PMU-PCA3 score at 90%, its specificity was 79% in men with BP and 69% in men with isolated HGPIN. The efficacy of the PMU-PCA3 score to rule out PCa in men with HGPIN is lower than in men with BP.

Common factor analysis versus principal component analysis: choice for symptom cluster research.

PubMed

Kim, Hee-Ju

2008-03-01

The purpose of this paper is to examine differences between two factor analytical methods and their relevance for symptom cluster research: common factor analysis (CFA) versus principal component analysis (PCA). Literature was critically reviewed to elucidate the differences between CFA and PCA. A secondary analysis (N = 84) was utilized to show the actual result differences from the two methods. CFA analyzes only the reliable common variance of data, while PCA analyzes all the variance of data. An underlying hypothetical process or construct is involved in CFA but not in PCA. PCA tends to increase factor loadings especially in a study with a small number of variables and/or low estimated communality. Thus, PCA is not appropriate for examining the structure of data. If the study purpose is to explain correlations among variables and to examine the structure of the data (this is usual for most cases in symptom cluster research), CFA provides a more accurate result. If the purpose of a study is to summarize data with a smaller number of variables, PCA is the choice. PCA can also be used as an initial step in CFA because it provides information regarding the maximum number and nature of factors. In using factor analysis for symptom cluster research, several issues need to be considered, including subjectivity of solution, sample size, symptom selection, and level of measure.

Receptor modeling for source apportionment of polycyclic aromatic hydrocarbons in urban atmosphere.

PubMed

Singh, Kunwar P; Malik, Amrita; Kumar, Ranjan; Saxena, Puneet; Sinha, Sarita

2008-01-01

This study reports source apportionment of polycyclic aromatic hydrocarbons (PAHs) in particulate depositions on vegetation foliages near highway in the urban environment of Lucknow city (India) using the principal components analysis/absolute principal components scores (PCA/APCS) receptor modeling approach. The multivariate method enables identification of major PAHs sources along with their quantitative contributions with respect to individual PAH. The PCA identified three major sources of PAHs viz. combustion, vehicular emissions, and diesel based activities. The PCA/APCS receptor modeling approach revealed that the combustion sources (natural gas, wood, coal/coke, biomass) contributed 19-97% of various PAHs, vehicular emissions 0-70%, diesel based sources 0-81% and other miscellaneous sources 0-20% of different PAHs. The contributions of major pyrolytic and petrogenic sources to the total PAHs were 56 and 42%, respectively. Further, the combustion related sources contribute major fraction of the carcinogenic PAHs in the study area. High correlation coefficient (R2 > 0.75 for most PAHs) between the measured and predicted concentrations of PAHs suggests for the applicability of the PCA/APCS receptor modeling approach for estimation of source contribution to the PAHs in particulates.

Binding Isotherms and Time Courses Readily from Magnetic Resonance.

PubMed

Xu, Jia; Van Doren, Steven R

2016-08-16

Evidence is presented that binding isotherms, simple or biphasic, can be extracted directly from noninterpreted, complex 2D NMR spectra using principal component analysis (PCA) to reveal the largest trend(s) across the series. This approach renders peak picking unnecessary for tracking population changes. In 1:1 binding, the first principal component captures the binding isotherm from NMR-detected titrations in fast, slow, and even intermediate and mixed exchange regimes, as illustrated for phospholigand associations with proteins. Although the sigmoidal shifts and line broadening of intermediate exchange distorts binding isotherms constructed conventionally, applying PCA directly to these spectra along with Pareto scaling overcomes the distortion. Applying PCA to time-domain NMR data also yields binding isotherms from titrations in fast or slow exchange. The algorithm readily extracts from magnetic resonance imaging movie time courses such as breathing and heart rate in chest imaging. Similarly, two-step binding processes detected by NMR are easily captured by principal components 1 and 2. PCA obviates the customary focus on specific peaks or regions of images. Applying it directly to a series of complex data will easily delineate binding isotherms, equilibrium shifts, and time courses of reactions or fluctuations.

Analyzing brain networks with PCA and conditional Granger causality.

PubMed

Zhou, Zhenyu; Chen, Yonghong; Ding, Mingzhou; Wright, Paul; Lu, Zuhong; Liu, Yijun

2009-07-01

Identifying directional influences in anatomical and functional circuits presents one of the greatest challenges for understanding neural computations in the brain. Granger causality mapping (GCM) derived from vector autoregressive models of data has been employed for this purpose, revealing complex temporal and spatial dynamics underlying cognitive processes. However, the traditional GCM methods are computationally expensive, as signals from thousands of voxels within selected regions of interest (ROIs) are individually processed, and being based on pairwise Granger causality, they lack the ability to distinguish direct from indirect connectivity among brain regions. In this work a new algorithm called PCA based conditional GCM is proposed to overcome these problems. The algorithm implements the following two procedures: (i) dimensionality reduction in ROIs of interest with principle component analysis (PCA), and (ii) estimation of the direct causal influences in local brain networks, using conditional Granger causality. Our results show that the proposed method achieves greater accuracy in detecting network connectivity than the commonly used pairwise Granger causality method. Furthermore, the use of PCA components in conjunction with conditional GCM greatly reduces the computational cost relative to the use of individual voxel time series. Copyright 2009 Wiley-Liss, Inc

The Effect of Phenazine-1-Carboxylic Acid on Mycelial Growth of Botrytis cinerea Produced by Pseudomonas aeruginosa LV Strain

PubMed Central

Simionato, Ane S.; Navarro, Miguel O. P.; de Jesus, Maria L. A.; Barazetti, André R.; da Silva, Caroline S.; Simões, Glenda C.; Balbi-Peña, Maria I.; de Mello, João C. P.; Panagio, Luciano A.; de Almeida, Ricardo S. C.; Andrade, Galdino; de Oliveira, Admilton G.

2017-01-01

One of the most important postharvest plant pathogens that affect strawberries, grapes and tomatoes is Botrytis cinerea, known as gray mold. The fungus remains in latent form until spore germination conditions are good, making infection control difficult, causing great losses in the whole production chain. This study aimed to purify and identify phenazine-1-carboxylic acid (PCA) produced by the Pseudomonas aeruginosa LV strain and to determine its antifungal activity against B. cinerea. The compounds produced were extracted with dichloromethane and passed through a chromatographic process. The purity level of PCA was determined by reversed-phase high-performance liquid chromatography semi-preparative. The structure of PCA was confirmed by nuclear magnetic resonance and electrospray ionization mass spectrometry. Antifungal activity was determined by the dry paper disk and minimum inhibitory concentration (MIC) methods and identified by scanning electron microscopy and confocal microscopy. The results showed that PCA inhibited mycelial growth, where MIC was 25 μg mL-1. Microscopic analysis revealed a reduction in exopolysaccharide (EPS) formation, showing distorted and damaged hyphae of B. cinerea. The results suggested that PCA has a high potential in the control of B. cinerea and inhibition of EPS (important virulence factor). This natural compound is a potential alternative to postharvest control of gray mold disease. PMID:28659907

Analysis of the principal component algorithm in phase-shifting interferometry.

PubMed

Vargas, J; Quiroga, J Antonio; Belenguer, T

2011-06-15

We recently presented a new asynchronous demodulation method for phase-sampling interferometry. The method is based in the principal component analysis (PCA) technique. In the former work, the PCA method was derived heuristically. In this work, we present an in-depth analysis of the PCA demodulation method.

Computer-aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI.

PubMed

Song, Yang; Zhang, Yu-Dong; Yan, Xu; Liu, Hui; Zhou, Minxiong; Hu, Bingwen; Yang, Guang

2018-04-16

Deep learning is the most promising methodology for automatic computer-aided diagnosis of prostate cancer (PCa) with multiparametric MRI (mp-MRI). To develop an automatic approach based on deep convolutional neural network (DCNN) to classify PCa and noncancerous tissues (NC) with mp-MRI. Retrospective. In all, 195 patients with localized PCa were collected from a PROSTATEx database. In total, 159/17/19 patients with 444/48/55 observations (215/23/23 PCas and 229/25/32 NCs) were randomly selected for training/validation/testing, respectively. T 2 -weighted, diffusion-weighted, and apparent diffusion coefficient images. A radiologist manually labeled the regions of interest of PCas and NCs and estimated the Prostate Imaging Reporting and Data System (PI-RADS) scores for each region. Inspired by VGG-Net, we designed a patch-based DCNN model to distinguish between PCa and NCs based on a combination of mp-MRI data. Additionally, an enhanced prediction method was used to improve the prediction accuracy. The performance of DCNN prediction was tested using a receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Moreover, the predicted result was compared with the PI-RADS score to evaluate its clinical value using decision curve analysis. Two-sided Wilcoxon signed-rank test with statistical significance set at 0.05. The DCNN produced excellent diagnostic performance in distinguishing between PCa and NC for testing datasets with an AUC of 0.944 (95% confidence interval: 0.876-0.994), sensitivity of 87.0%, specificity of 90.6%, PPV of 87.0%, and NPV of 90.6%. The decision curve analysis revealed that the joint model of PI-RADS and DCNN provided additional net benefits compared with the DCNN model and the PI-RADS scheme. The proposed DCNN-based model with enhanced prediction yielded high performance in statistical analysis, suggesting that DCNN could be used in computer-aided diagnosis (CAD) for PCa classification. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Androgen receptor (AR) cistrome in prostate differentiation and cancer progression.

PubMed

Wang, Fengtian; Koul, Hari K

2017-01-01

Despite the progress in development of better AR-targeted therapies for prostate cancer (PCa), there is no curative therapy for castration-resistant prostate cancer (CRPC). Therapeutic resistance in PCa can be characterized in two broad categories of AR therapy resistance: the first and most prevalent one involves restoration of AR activity despite AR targeted therapy, and the second one involves tumor progression despite blockade of AR activity. As such AR remains the most attractive drug target for CRPC. Despite its oncogenic role, AR signaling also contributes to the maturation and differentiation of prostate luminal cells during development. Recent evidence suggests that AR cistrome is altered in advanced PCa. Alteration in AR may result from AR amplification, alternative splicing, mutations, post-translational modification of AR, and altered expression of AR co-factors. We reasoned that such alterations would result in the transcription of disparate AR target genes and as such may contribute to the emergence of castration-resistance. In the present study, we evaluated the expression of genes associated with canonical or non-canonical AR cistrome in relationship with PCa progression and prostate development by analyzing publicly available datasets. We discovered a transcription switch from canonical AR cistrome target genes to the non-canonical AR cistrome target genes during PCa progression. Using Gene Set Enrichment Analysis (GSEA), we discovered that canonical AR cistrome target genes are enriched in indolent PCa patients and the loss of canonical AR cistrome is associated with tumor metastasis and poor clinical outcome. Analysis of the datasets involving prostate development, revealed that canonical AR cistrome target genes are significantly enriched in prostate luminal cells and can distinguish luminal cells from basal cells, suggesting a pivotal role for canonical AR cistrome driven genes in prostate development. These data suggest that the expression of canonical AR cistrome related genes play an important role in maintaining the prostate luminal cell identity and might restrict the lineage plasticity observed in lethal PCa. Understanding the molecular mechanisms that dictate AR cistrome may lead to development of new therapeutic strategies aimed at restoring canonical AR cistrome, rewiring the oncogenic AR signaling and overcome resistance to AR targeted therapies.

Transcriptome alteration in Phytophthora infestans in response to phenazine-1-carboxylic acid production by Pseudomonas fluorescens strain LBUM223.

PubMed

Roquigny, Roxane; Novinscak, Amy; Arseneault, Tanya; Joly, David L; Filion, Martin

2018-06-19

Phytophthora infestans is responsible for late blight, one of the most important potato diseases. Phenazine-1-carboxylic acid (PCA)-producing Pseudomonas fluorescens strain LBUM223 isolated in our laboratory shows biocontrol potential against various plant pathogens. To characterize the effect of LBUM223 on the transcriptome of P. infestans, we conducted an in vitro time-course study. Confrontational assay was performed using P. infestans inoculated alone (control) or with LBUM223, its phzC- isogenic mutant (not producing PCA), or exogenically applied PCA. Destructive sampling was performed at 6, 9 and 12 days and the transcriptome of P. infestans was analysed using RNA-Seq. The expression of a subset of differentially expressed genes was validated by RT-qPCR. Both LBUM223 and exogenically applied PCA significantly repressed P. infestans' growth at all times. Compared to the control treatment, transcriptomic analyses showed that the percentages of all P. infestans' genes significantly altered by LBUM223 and exogenically applied PCA increased as time progressed, from 50 to 61% and from to 32 to 46%, respectively. When applying an absolute cut-off value of 3 fold change or more for all three harvesting times, 207 genes were found significantly differentially expressed by PCA, either produced by LBUM223 or exogenically applied. Gene ontology analysis revealed that both treatments altered the expression of key functional genes involved in major functions like phosphorylation mechanisms, transmembrane transport and oxidoreduction activities. Interestingly, even though no host plant tissue was present in the in vitro system, PCA also led to the overexpression of several genes encoding effectors. The mutant only slightly repressed P. infestans' growth and barely altered its transcriptome. Our study suggests that PCA is involved in P. infestans' growth repression and led to important transcriptomic changes by both up- and down-regulating gene expression in P. infestans over time. Different metabolic functions were altered and many effectors were found to be upregulated, suggesting their implication in biocontrol.

Expression of the TPα and TPβ isoforms of the thromboxane prostanoid receptor (TP) in prostate cancer: clinical significance and diagnostic potential.

PubMed

Mulvaney, Eamon P; Shilling, Christine; Eivers, Sarah B; Perry, Antoinette S; Bjartell, Anders; Kay, Elaine W; Watson, R William; Kinsella, B Therese

2016-11-08

The prostanoid thromboxane (TX)A2 plays a central role in haemostasis and is increasingly implicated in cancer progression. TXA2 signals through two T Prostanoid receptor (TP) isoforms termed TPα and TPβ, with both encoded by the TBXA2R gene. Despite exhibiting several functional and regulatory differences, the role of the individual TP isoforms in neoplastic diseases is largely unknown.This study evaluated expression of the TPα and TPβ isoforms in tumour microarrays of the benign prostate and different pathological (Gleason) grades of prostate cancer (PCa). Expression of TPβ was significantly increased in PCa relative to benign tissue and strongly correlated with increasing Gleason grade. Furthermore, higher TPβ expression was associated with increased risk of biochemical recurrence (BCR) and significantly shorter disease-free survival time in patients post-surgery. While TPα was more variably expressed than TPβ in PCa, increased/high TPα expression within the tumour also trended toward increased BCR and shorter disease-free survival time. Comparative genomic CpG DNA methylation analysis revealed substantial differences in the extent of methylation of the promoter regions of the TBXA2R that specifically regulate expression of TPα and TPβ, respectively, both in benign prostate and in clinically-derived tissue representative of precursor lesions and progressive stages of PCa. Collectively, TPα and TPβ expression is differentially regulated both in the benign and tumourigenic prostate, and coincides with clinical pathology and altered CpG methylation of the TBXA2R gene. Analysis of TPβ, or a combination of TPα/TPβ, expression levels may have significant clinical potential as a diagnostic biomarker and predictor of PCa disease recurrence.

Motivation for HPV Vaccination Among Young Adult Men: Validation of TTM Decisional Balance and Self-Efficacy Constructs.

PubMed

Fernandez, Anne C; Amoyal, Nicole R; Paiva, Andrea L; Prochaska, James O

2016-01-01

In the United States, 36% of human papillomavirus (HPV)-related cancers occur among men. HPV vaccination can substantially reduce the risk of HPV infection; however, the vast majority of men are unvaccinated. This study developed and validated transtheoretical model-based measures for HPV vaccination in young adult men. Cross-sectional measurement development. Online survey of young adult men. Three hundred twenty-nine mostly college-attending men, ages 18 to 26. Stage of change, decisional balance (pros/cons), and self-efficacy. The sample was randomly split into halves for exploratory principal components analysis (PCA), followed by confirmatory factor analyses (CFA) to test measurement models. Multivariate analyses examined relationships between scales. For decisional balance, PCA revealed two uncorrelated five-item factors (pros α = .78; cons α = .83). For the self-efficacy scale, PCA revealed a single-factor solution (α = .83). CFA confirmed that the two-factor uncorrelated model for decisional balance and a single-factor model for self-efficacy. Follow-up analyses of variance supported the theoretically predicted relationships between stage of change, pros, and self-efficacy. This study resulted in reliable and valid measures of pros and self-efficacy for HPV vaccination that can be used in future clinical research.

The development of summary components for the Disablement in the Physically Active scale in collegiate athletes.

PubMed

Houston, Megan N; Hoch, Johanna M; Van Lunen, Bonnie L; Hoch, Matthew C

2015-11-01

The Disablement in the Physically Active scale (DPA) is a generic patient-reported outcome designed to evaluate constructs of disability in physically active populations. The purpose of this study was to analyze the DPA scale structure for summary components. Four hundred and fifty-six collegiate athletes completed a demographic form and the DPA. A principal component analysis (PCA) was conducted with oblique rotation. Factors with eigenvalues >1 that explained >5 % of the variance were retained. The PCA revealed a two-factor structure consistent with paradigms used to develop the original DPA. Items 1-12 loaded on Factors 1 and Items 13-16 loaded on Factor 2. Items 1-12 pertain to impairment, activity limitations, and participation restrictions. Items 13-16 address psychosocial and emotional well-being. Consideration of item content suggested Factor 1 concerned physical function, while Factor 2 concerned mental well-being. Thus, items clustered around Factor 1 and 2 were identified as physical (DPA-PSC) and mental (DPA-MSC) summary components, respectively. Together, the factors accounted for 65.1 % of the variance. The PCA revealed a two-factor structure for the DPA that resulted in DPA-PSC and DPA-MSC. Analyzing the DPA as separate constructs may provide distinct information that could help to prescribe treatment and rehabilitation strategies.

Is Eotaxin-1 a serum and urinary biomarker for prostate cancer detection and recurrence?

PubMed

Heidegger, Isabel; Höfer, Julia; Luger, Markus; Pichler, Renate; Klocker, Helmut; Horninger, Wolfgang; Steiner, Eberhard; Jochberger, Stefan; Culig, Zoran

2015-12-01

Eotaxin-1 (CCL11) is a protein expressed in various tissues influencing immunoregulatory processes by acting as selective eosinophil chemo-attractant. In prostate cancer (PCa), the expression and functional role of CCL11 have not been intensively investigated so far. Therefore, the aim of the present study was to investigate the diagnostic or prognostic potential of Eotaxin-1 in PCa patients. We analyzed serum from 140 patients who have undergone prostate biopsy due to elevated prostate-specific antigen (PSA) levels as well as serum of 20 individuals with PSA levels < 1ng/ml (healthy control group). Moreover, 40 urine samples were analyzed. A custom-made Q-Plex array ELISA (Quansys Biosciences) for the detection of Eotaxin-1 was performed and Q-View Software used for quantification. In addition, clinical courses of patients documented in our Prostate Biobank database were analyzed. ROC and survival analyses were used to determine the diagnostic and prognostic power of Eotaxin-1 levels. Serum Eotaxin-1 levels were significantly decreased in PCa (P = 0.006) as well as in benign prostate hyperplasia (P = 0.0006) compared to the control group. ROC analysis revealed that Eotaxin-1 is a significant marker to distinguish PCa from disease-free prostate. Moreover, we found that Eotaxin-1 expression is significantly decreased in Gleason score (GS) 6 (P = 0.0135) and GS 8 (P = 0.0057) patients compared to samples of healthy men, respectively. However, PCa aggressiveness was not predictable by Eotaxin-1 levels. In line with serum analyses, urine Eotaxin-1 was significantly decreased in patients with PCa compared to cancer-free individuals (P = 0.0185) but was not different between cancers of different GS. Patientś follow-up analyses showed no significant correlation between serum Eotaxin-1 levels and time to biochemical recurrence. Survival analyses also revealed no significant changes in progression-free survival among low (≤ 112.2 pg/ml) and high (> 112.2 pg/ml) Eotaxin-1 serum levels. Although this study has not established a prognostic role of Eotaxin-1 in PCa patients, this chemokine may serve as a diagnostic marker to distinguish between disease-free prostate and cancer. © 2015 Wiley Periodicals, Inc.

Strain Transient Detection Techniques: A Comparison of Source Parameter Inversions of Signals Isolated through Principal Component Analysis (PCA), Non-Linear PCA, and Rotated PCA

NASA Astrophysics Data System (ADS)

Lipovsky, B.; Funning, G. J.

2009-12-01

We compare several techniques for the analysis of geodetic time series with the ultimate aim to characterize the physical processes which are represented therein. We compare three methods for the analysis of these data: Principal Component Analysis (PCA), Non-Linear PCA (NLPCA), and Rotated PCA (RPCA). We evaluate each method by its ability to isolate signals which may be any combination of low amplitude (near noise level), temporally transient, unaccompanied by seismic emissions, and small scale with respect to the spatial domain. PCA is a powerful tool for extracting structure from large datasets which is traditionally realized through either the solution of an eigenvalue problem or through iterative methods. PCA is an transformation of the coordinate system of our data such that the new "principal" data axes retain maximal variance and minimal reconstruction error (Pearson, 1901; Hotelling, 1933). RPCA is achieved by an orthogonal transformation of the principal axes determined in PCA. In the analysis of meteorological data sets, RPCA has been seen to overcome domain shape dependencies, correct for sampling errors, and to determine principal axes which more closely represent physical processes (e.g., Richman, 1986). NLPCA generalizes PCA such that principal axes are replaced by principal curves (e.g., Hsieh 2004). We achieve NLPCA through an auto-associative feed-forward neural network (Scholz, 2005). We show the geophysical relevance of these techniques by application of each to a synthetic data set. Results are compared by inverting principal axes to determine deformation source parameters. Temporal variability in source parameters, estimated by each method, are also compared.

Proteomic Profiling of Exosomes Leads to the Identification of Novel Biomarkers for Prostate Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duijvesz, Diederick; Burnum-Johnson, Kristin E.; Gritsenko, Marina A.

Introduction: Current markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, biomarker discovery from body fluids is often hampered by the high abundance of many proteins unrelated to disease. An attractive alternative biomarker discovery approach is the isolation of small vesicles (exosomes, ~100 nm). They contain proteins that are specific to the tissue from which they are derived and therefore can be considered as treasure chests for disease-specific marker discovery. Profiling prostate cancer-derived exosomes could reveal new markers for this malignancy. Materials and Methods: Exosomes were isolated from 2 immortalized primary prostate epithelial cellsmore » (PNT2C2 and RWPE-1) and 2 PCa cell lines (PC346C and VCaP) by ultracentrifugation. Proteomic analyses utilized a nanoLC coupled with an LTQ-Orbitrap operated in tandem MS (MS/MS) mode, followed by the Accurate Mass and Time (AMT) tag approach. Exosomal proteins were validated by Western blotting. A Tissue Micro Array, containing 481 different PCa samples (radical prostatectomy), was used to correlate candidate markers with several clinical-pathological parameters such as PSA, Gleason score, biochemical recurrence, and (PCa-related) death. Results: Proteomic characterization resulted in the identification of 263 proteins by at least 2 peptides. Specifically analysis of exosomes from PNT2C2, RWPE-1, PC346C, and VCaP identified 248, 233, 169, and 216 proteins, respectively. Statistical analyses revealed 52 proteins differently expressed between PCa and control cells, 9 of which were more abundant in PCa. Validation by Western blotting confirmed a higher abundance of FASN, XPO1 and PDCD6IP (ALIX) in PCa exosomes. The Tissue Micro 4 Array showed strong correlation of higher Gleason scores and local recurrence with increased cytoplasmic XPO1 (P<0.001). Conclusions: Differentially abundant proteins of cell line-derived exosomes make a clear subdivision between benign and malignant origin. Validation showed a preferential abundance of PDCD6IP, FASN and XPO1. Cytoplasmic XPO1 is the most promising candidate biomarker.« less

A pattern recognition approach to transistor array parameter variance

NASA Astrophysics Data System (ADS)

da F. Costa, Luciano; Silva, Filipi N.; Comin, Cesar H.

2018-06-01

The properties of semiconductor devices, including bipolar junction transistors (BJTs), are known to vary substantially in terms of their parameters. In this work, an experimental approach, including pattern recognition concepts and methods such as principal component analysis (PCA) and linear discriminant analysis (LDA), was used to experimentally investigate the variation among BJTs belonging to integrated circuits known as transistor arrays. It was shown that a good deal of the devices variance can be captured using only two PCA axes. It was also verified that, though substantially small variation of parameters is observed for BJT from the same array, larger variation arises between BJTs from distinct arrays, suggesting the consideration of device characteristics in more critical analog designs. As a consequence of its supervised nature, LDA was able to provide a substantial separation of the BJT into clusters, corresponding to each transistor array. In addition, the LDA mapping into two dimensions revealed a clear relationship between the considered measurements. Interestingly, a specific mapping suggested by the PCA, involving the total harmonic distortion variation expressed in terms of the average voltage gain, yielded an even better separation between the transistor array clusters. All in all, this work yielded interesting results from both semiconductor engineering and pattern recognition perspectives.

Near infrared diffuse reflection and laser-induced fluorescence spectroscopy for myocardial tissue characterisation

NASA Astrophysics Data System (ADS)

Nilsson, A. M. K.; Heinrich, D.; Olajos, J.; Andersson-Engels, S.

1997-10-01

In order to evaluate the potential of cardiovascular tissue characterisation using near-infrared (NIR) spectroscopy, spectra in a previously unexplored wavelength region 0.8-2.3 μm were recorded from various pig heart tissue samples in vitro: normal myocardium (with and without endo/epicardium), aorta, fatty and fibrous heart tissue. The spectra were analysed with principal component analysis (PCA), revealing several spectroscopically characteristic features enabling tissue classification. Several of the identified spectral features could be attributed to specific tissue constituents by comparing the tissue signals with spectra obtained from water, elastin, collagen and cholesterol as well as with published data. The results obtained with the NIR spectroscopy technique in terms of its potential to classify different tissue types were compared with those from laser-induced fluorescence (LIF) using 337 nm excitation. LIF and NIR spectroscopy can in combination with PCA be used to discriminate between all previously mentioned tissue groups, apart from fatty versus fibrous tissue (LIF) and aorta versus fibrous tissue (NIR), respectively. The NIR analysis was improved by focusing the PCA to the wavelength segment 2.0-2.3 μm, resulting in successful spectral characterisation of all cardiovascular tissue groups.

Does adding ketamine to morphine patient-controlled analgesia safely improve post-thoracotomy pain?

PubMed

Mathews, Timothy J; Churchhouse, Antonia M D; Housden, Tessa; Dunning, Joel

2012-02-01

A best evidence topic in thoracic surgery was written according to a structured protocol. The question addressed was 'is the addition of ketamine to morphine patient-controlled analgesia (PCA) following thoracic surgery superior to morphine alone'. Altogether 201 papers were found using the reported search, of which nine represented the best evidence to answer the clinical question. The authors, journal, date and country of publication, patient group studied, study type, relevant outcomes and results of these papers are tabulated. This consisted of one systematic review of PCA morphine with ketamine (PCA-MK) trials, one meta-analysis of PCA-MK trials, four randomized controlled trials of PCA-MK, one meta-analysis of trials using a variety of peri-operative ketamine regimes and two cohort studies of PCA-MK. Main outcomes measured included pain score rated on visual analogue scale, morphine consumption and incidence of psychotomimetic side effects/hallucination. Two papers reported the measurements of respiratory function. This evidence shows that adding ketamine to morphine PCA is safe, with a reported incidence of hallucination requiring intervention of 2.9%, and a meta-analysis finding an incidence of all central nervous system side effects of 18% compared with 15% with morphine alone, P = 0.31, RR 1.27 with 95% CI (0.8-2.01). All randomized controlled trials of its use following thoracic surgery found no hallucination or psychological side effect. All five studies in thoracic surgery (n = 243) found reduced morphine requirements with PCA-MK. Pain scores were significantly lower in PCA-MK patients in thoracic surgery papers, with one paper additionally reporting increased patient satisfaction. However, no significant improvement was found in a meta-analysis of five papers studying PCA-MK in a variety of surgical settings. Both papers reporting respiratory outcomes found improved oxygen saturations and PaCO(2) levels in PCA-MK patients following thoracic surgery. We conclude that adding low-dose ketamine to morphine PCA is safe and post-thoracotomy may provide better pain control than PCA with morphine alone (PCA-MO), with reduced morphine consumption and possible improvement in respiratory function. These studies thus support the routine use of PCA-MK instead of PCA-MO to improve post-thoracotomy pain control.

Principal component analysis to assess the efficiency and mechanism for enhanced coagulation of natural algae-laden water using a novel dual coagulant system.

PubMed

Ou, Hua-Se; Wei, Chao-Hai; Deng, Yang; Gao, Nai-Yun; Ren, Yuan; Hu, Yun

2014-02-01

A novel dual coagulant system of polyaluminum chloride sulfate (PACS) and polydiallyldimethylammonium chloride (PDADMAC) was used to treat natural algae-laden water from Meiliang Gulf, Lake Taihu. PACS (Aln(OH)mCl3n-m-2k(SO4)k) has a mass ratio of 10 %, a SO4 (2-)/Al3 (+) mole ratio of 0.0664, and an OH/Al mole ratio of 2. The PDADMAC ([C8H16NCl]m) has a MW which ranges from 5 × 10(5) to 20 × 10(5) Da. The variations of contaminants in water samples during treatments were estimated in the form of principal component analysis (PCA) factor scores and conventional variables (turbidity, DOC, etc.). Parallel factor analysis determined four chromophoric dissolved organic matters (CDOM) components, and PCA identified four integrated principle factors. PCA factor 1 had significant correlations with chlorophyll-a (r=0.718), protein-like CDOM C1 (0.689), and C2 (0.756). Factor 2 correlated with UV254 (0.672), humic-like CDOM component C3 (0.716), and C4 (0.758). Factors 3 and 4 had correlations with NH3-N (0.748) and T-P (0.769), respectively. The variations of PCA factors scores revealed that PACS contributed less aluminum dissolution than PAC to obtain equivalent removal efficiency of contaminants. This might be due to the high cationic charge and pre-hydrolyzation of PACS. Compared with PACS coagulation (20 mg L(-1)), the removal of PCA factors 1, 2, and 4 increased 45, 33, and 12 %, respectively, in combined PACS-PDADMAC treatment (0.8 mg L(-1) +20 mg L(-1)). Since PAC contained more Al (0.053 g/1 g) than PACS (0.028 g/1 g), the results indicated that PACS contributed less Al dissolution into the water to obtain equivalent removal efficiency.

Soy Consumption and the Risk of Prostate Cancer: An Updated Systematic Review and Meta-Analysis

PubMed Central

Ranard, Katherine M.; Jeon, Sookyoung; Erdman, John W.

2018-01-01

Prostate cancer (PCa) is the second most commonly diagnosed cancer in men, accounting for 15% of all cancers in men worldwide. Asian populations consume soy foods as part of a regular diet, which may contribute to the lower PCa incidence observed in these countries. This meta-analysis provides a comprehensive updated analysis that builds on previously published meta-analyses, demonstrating that soy foods and their isoflavones (genistein and daidzein) are associated with a lower risk of prostate carcinogenesis. Thirty articles were included for analysis of the potential impacts of soy food intake, isoflavone intake, and circulating isoflavone levels, on both primary and advanced PCa. Total soy food (p < 0.001), genistein (p = 0.008), daidzein (p = 0.018), and unfermented soy food (p < 0.001) intakes were significantly associated with a reduced risk of PCa. Fermented soy food intake, total isoflavone intake, and circulating isoflavones were not associated with PCa risk. Neither soy food intake nor circulating isoflavones were associated with advanced PCa risk, although very few studies currently exist to examine potential associations. Combined, this evidence from observational studies shows a statistically significant association between soy consumption and decreased PCa risk. Further studies are required to support soy consumption as a prophylactic dietary approach to reduce PCa carcinogenesis. PMID:29300347

Dietary flavonoid fisetin increases abundance of high-molecular-mass hyaluronan conferring resistance to prostate oncogenesis.

PubMed

Lall, Rahul K; Syed, Deeba N; Khan, Mohammad Imran; Adhami, Vaqar M; Gong, Yuansheng; Lucey, John A; Mukhtar, Hasan

2016-09-01

We and others have shown previously that fisetin, a plant flavonoid, has therapeutic potential against many cancer types. Here, we examined the probable mechanism of its action in prostate cancer (PCa) using a global metabolomics approach. HPLC-ESI-MS analysis of tumor xenografts from fisetin-treated animals identified several metabolic targets with hyaluronan (HA) as the most affected. Efficacy of fisetin on HA was then evaluated in vitro and also in vivo in the transgenic TRAMP mouse model of PCa. Size exclusion chromatography-multiangle laser light scattering (SEC-MALS) was performed to analyze the molar mass (Mw) distribution of HA. Fisetin treatment downregulated intracellular and secreted HA levels both in vitro and in vivo Fisetin inhibited HA synthesis and degradation enzymes, which led to cessation of HA synthesis and also repressed the degradation of the available high-molecular-mass (HMM)-HA. SEC-MALS analysis of intact HA fragment size revealed that cells and animals have more abundance of HMM-HA and less of low-molecular-mass (LMM)-HA upon fisetin treatment. Elevated HA levels have been shown to be associated with disease progression in certain cancer types. Biological responses triggered by HA mainly depend on the HA polymer length where HMM-HA represses mitogenic signaling and has anti-inflammatory properties whereas LMM-HA promotes proliferation and inflammation. Similarly, Mw analysis of secreted HA fragment size revealed less HMM-HA is secreted that allowed more HMM-HA to be retained within the cells and tissues. Our findings establish that fisetin is an effective, non-toxic, potent HA synthesis inhibitor, which increases abundance of antiangiogenic HMM-HA and could be used for the management of PCa. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Local coexistence of VO 2 phases revealed by deep data analysis

DOE PAGES

Strelcov, Evgheni; Ievlev, Anton; Tselev, Alexander; ...

2016-07-07

We report a synergistic approach of micro-Raman spectroscopic mapping and deep data analysis to study the distribution of crystallographic phases and ferroelastic domains in a defected Al-doped VO 2 microcrystal. Bayesian linear unmixing revealed an uneven distribution of the T phase, which is stabilized by the surface defects and uneven local doping that went undetectable by other classical analysis techniques such as PCA and SIMPLISMA. This work demonstrates the impact of information recovery via statistical analysis and full mapping in spectroscopic studies of vanadium dioxide systems, which is commonly substituted by averaging or single point-probing approaches, both of which suffermore » from information misinterpretation due to low resolving power.« less

Multilevel principal component analysis (mPCA) in shape analysis: A feasibility study in medical and dental imaging.

PubMed

Farnell, D J J; Popat, H; Richmond, S

2016-06-01

Methods used in image processing should reflect any multilevel structures inherent in the image dataset or they run the risk of functioning inadequately. We wish to test the feasibility of multilevel principal components analysis (PCA) to build active shape models (ASMs) for cases relevant to medical and dental imaging. Multilevel PCA was used to carry out model fitting to sets of landmark points and it was compared to the results of "standard" (single-level) PCA. Proof of principle was tested by applying mPCA to model basic peri-oral expressions (happy, neutral, sad) approximated to the junction between the mouth/lips. Monte Carlo simulations were used to create this data which allowed exploration of practical implementation issues such as the number of landmark points, number of images, and number of groups (i.e., "expressions" for this example). To further test the robustness of the method, mPCA was subsequently applied to a dental imaging dataset utilising landmark points (placed by different clinicians) along the boundary of mandibular cortical bone in panoramic radiographs of the face. Changes of expression that varied between groups were modelled correctly at one level of the model and changes in lip width that varied within groups at another for the Monte Carlo dataset. Extreme cases in the test dataset were modelled adequately by mPCA but not by standard PCA. Similarly, variations in the shape of the cortical bone were modelled by one level of mPCA and variations between the experts at another for the panoramic radiographs dataset. Results for mPCA were found to be comparable to those of standard PCA for point-to-point errors via miss-one-out testing for this dataset. These errors reduce with increasing number of eigenvectors/values retained, as expected. We have shown that mPCA can be used in shape models for dental and medical image processing. mPCA was found to provide more control and flexibility when compared to standard "single-level" PCA. Specifically, mPCA is preferable to "standard" PCA when multiple levels occur naturally in the dataset. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Modes and emergent time scales of embayed beach dynamics

NASA Astrophysics Data System (ADS)

Ratliff, Katherine M.; Murray, A. Brad

2014-10-01

In this study, we use a simple numerical model (the Coastline Evolution Model) to explore alongshore transport-driven shoreline dynamics within generalized embayed beaches (neglecting cross-shore effects). Using principal component analysis (PCA), we identify two primary orthogonal modes of shoreline behavior that describe shoreline variation about its unchanging mean position: the rotation mode, which has been previously identified and describes changes in the mean shoreline orientation, and a newly identified breathing mode, which represents changes in shoreline curvature. Wavelet analysis of the PCA mode time series reveals characteristic time scales of these modes (typically years to decades) that emerge within even a statistically constant white-noise wave climate (without changes in external forcing), suggesting that these time scales can arise from internal system dynamics. The time scales of both modes increase linearly with shoreface depth, suggesting that the embayed beach sediment transport dynamics exhibit a diffusive scaling.

Nonlinear Principal Components Analysis: Introduction and Application

ERIC Educational Resources Information Center

Linting, Marielle; Meulman, Jacqueline J.; Groenen, Patrick J. F.; van der Koojj, Anita J.

2007-01-01

The authors provide a didactic treatment of nonlinear (categorical) principal components analysis (PCA). This method is the nonlinear equivalent of standard PCA and reduces the observed variables to a number of uncorrelated principal components. The most important advantages of nonlinear over linear PCA are that it incorporates nominal and ordinal…

The fractal characteristic of facial anthropometric data for developing PCA fit test panels for youth born in central China.

PubMed

Yang, Lei; Wei, Ran; Shen, Henggen

2017-01-01

New principal component analysis (PCA) respirator fit test panels had been developed for current American and Chinese civilian workers based on anthropometric surveys. The PCA panels used the first two principal components (PCs) obtained from a set of 10 facial dimensions. Although the PCA panels for American and Chinese subjects adopted the bivairate framework with two PCs, the number of the PCs retained in the PCA analysis was different between Chinese subjects and Americans. For the Chinese youth group, the third PC should be retained in the PCA analysis for developing new fit test panels. In this article, an additional number label (ANL) is used to explain the third PC in PCA analysis when the first two PCs are used to construct the PCA half-facepiece respirator fit test panel for Chinese group. The three-dimensional box-counting method is proposed to estimate the ANLs by calculating fractal dimensions of the facial anthropometric data of the Chinese youth. The linear regression coefficients of scale-free range R 2 are all over 0.960, which demonstrates that the facial anthropometric data of the Chinese youth has fractal characteristic. The youth subjects born in Henan province has an ANL of 2.002, which is lower than the composite facial anthropometric data of Chinese subjects born in many provinces. Hence, Henan youth subjects have the self-similar facial anthropometric characteristic and should use the particular ANL (2.002) as the important tool along with using the PCA panel. The ANL method proposed in this article not only provides a new methodology in quantifying the characteristics of facial anthropometric dimensions for any ethnic/racial group, but also extends the scope of PCA panel studies to higher dimensions.

Candida parapsilosis biofilm identification by Raman spectroscopy.

PubMed

Samek, Ota; Mlynariková, Katarina; Bernatová, Silvie; Ježek, Jan; Krzyžánek, Vladislav; Šiler, Martin; Zemánek, Pavel; Růžička, Filip; Holá, Veronika; Mahelová, Martina

2014-12-22

Colonies of Candida parapsilosis on culture plates were probed directly in situ using Raman spectroscopy for rapid identification of specific strains separated by a given time intervals (up to months apart). To classify the Raman spectra, data analysis was performed using the approach of principal component analysis (PCA). The analysis of the data sets generated during the scans of individual colonies reveals that despite the inhomogeneity of the biological samples unambiguous associations to individual strains (two biofilm-positive and two biofilm-negative) could be made.

Candida parapsilosis Biofilm Identification by Raman Spectroscopy

PubMed Central

Samek, Ota; Mlynariková, Katarina; Bernatová, Silvie; Ježek, Jan; Krzyžánek, Vladislav; Šiler, Martin; Zemánek, Pavel; Růžička, Filip; Holá, Veronika; Mahelová, Martina

2014-01-01

Colonies of Candida parapsilosis on culture plates were probed directly in situ using Raman spectroscopy for rapid identification of specific strains separated by a given time intervals (up to months apart). To classify the Raman spectra, data analysis was performed using the approach of principal component analysis (PCA). The analysis of the data sets generated during the scans of individual colonies reveals that despite the inhomogeneity of the biological samples unambiguous associations to individual strains (two biofilm-positive and two biofilm-negative) could be made. PMID:25535081

Time-dependent analysis of dosage delivery information for patient-controlled analgesia services.

PubMed

Kuo, I-Ting; Chang, Kuang-Yi; Juan, De-Fong; Hsu, Steen J; Chan, Chia-Tai; Tsou, Mei-Yung

2018-01-01

Pain relief always plays the essential part of perioperative care and an important role of medical quality improvement. Patient-controlled analgesia (PCA) is a method that allows a patient to self-administer small boluses of analgesic to relieve the subjective pain. PCA logs from the infusion pump consisted of a lot of text messages which record all events during the therapies. The dosage information can be extracted from PCA logs to provide easily understanding features. The analysis of dosage information with time has great help to figure out the variance of a patient's pain relief condition. To explore the trend of pain relief requirement, we developed a PCA dosage information generator (PCA DIG) to extract meaningful messages from PCA logs during the first 48 hours of therapies. PCA dosage information including consumption, delivery, infusion rate, and the ratio between demand and delivery is presented with corresponding values in 4 successive time frames. Time-dependent statistical analysis demonstrated the trends of analgesia requirements decreased gradually along with time. These findings are compatible with clinical observations and further provide valuable information about the strategy to customize postoperative pain management.

Utility of Metabolomics toward Assessing the Metabolic Basis of Quality Traits in Apple Fruit with an Emphasis on Antioxidants

PubMed Central

Cuthbertson, Daniel; Andrews, Preston K.; Reganold, John P.; Davies, Neal M.; Lange, B. Markus

2012-01-01

A gas chromatography–mass spectrometry approach was employed to evaluate the use of metabolite patterns to differentiate fruit from six commercially grown apple cultivars harvested in 2008. Principal component analysis (PCA) of apple fruit peel and flesh data indicated that individual cultivar replicates clustered together and were separated from all other cultivar samples. An independent metabolomics investigation with fruit harvested in 2003 confirmed the separate clustering of fruit from different cultivars. Further evidence for cultivar separation was obtained using a hierarchical clustering analysis. An evaluation of PCA component loadings revealed specific metabolite classes that contributed the most to each principal component, whereas a correlation analysis demonstrated that specific metabolites correlate directly with quality traits such as antioxidant activity, total phenolics, and total anthocyanins, which are important parameters in the selection of breeding germplasm. These data sets lay the foundation for elucidating the metabolic basis of commercially important fruit quality traits. PMID:22881116

Performance analysis of a Principal Component Analysis ensemble classifier for Emotiv headset P300 spellers.

PubMed

Elsawy, Amr S; Eldawlatly, Seif; Taher, Mohamed; Aly, Gamal M

2014-01-01

The current trend to use Brain-Computer Interfaces (BCIs) with mobile devices mandates the development of efficient EEG data processing methods. In this paper, we demonstrate the performance of a Principal Component Analysis (PCA) ensemble classifier for P300-based spellers. We recorded EEG data from multiple subjects using the Emotiv neuroheadset in the context of a classical oddball P300 speller paradigm. We compare the performance of the proposed ensemble classifier to the performance of traditional feature extraction and classifier methods. Our results demonstrate the capability of the PCA ensemble classifier to classify P300 data recorded using the Emotiv neuroheadset with an average accuracy of 86.29% on cross-validation data. In addition, offline testing of the recorded data reveals an average classification accuracy of 73.3% that is significantly higher than that achieved using traditional methods. Finally, we demonstrate the effect of the parameters of the P300 speller paradigm on the performance of the method.

Automated Classification and Analysis of Non-metallic Inclusion Data Sets

NASA Astrophysics Data System (ADS)

Abdulsalam, Mohammad; Zhang, Tongsheng; Tan, Jia; Webler, Bryan A.

2018-05-01

The aim of this study is to utilize principal component analysis (PCA), clustering methods, and correlation analysis to condense and examine large, multivariate data sets produced from automated analysis of non-metallic inclusions. Non-metallic inclusions play a major role in defining the properties of steel and their examination has been greatly aided by automated analysis in scanning electron microscopes equipped with energy dispersive X-ray spectroscopy. The methods were applied to analyze inclusions on two sets of samples: two laboratory-scale samples and four industrial samples from a near-finished 4140 alloy steel components with varying machinability. The laboratory samples had well-defined inclusions chemistries, composed of MgO-Al2O3-CaO, spinel (MgO-Al2O3), and calcium aluminate inclusions. The industrial samples contained MnS inclusions as well as (Ca,Mn)S + calcium aluminate oxide inclusions. PCA could be used to reduce inclusion chemistry variables to a 2D plot, which revealed inclusion chemistry groupings in the samples. Clustering methods were used to automatically classify inclusion chemistry measurements into groups, i.e., no user-defined rules were required.

Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model.

PubMed

Lin, Yuxin; Chen, Feifei; Shen, Li; Tang, Xiaoyu; Du, Cui; Sun, Zhandong; Ding, Huijie; Chen, Jiajia; Shen, Bairong

2018-05-21

Prostate cancer (PCa) is a fatal malignant tumor among males in the world and the metastasis is a leading cause for PCa death. Biomarkers are therefore urgently needed to detect PCa metastatic signature at the early time. MicroRNAs are small non-coding RNAs with the potential to be biomarkers for disease prediction. In addition, computer-aided biomarker discovery is now becoming an attractive paradigm for precision diagnosis and prognosis of complex diseases. In this study, we identified key microRNAs as biomarkers for predicting PCa metastasis based on network vulnerability analysis. We first extracted microRNAs and mRNAs that were differentially expressed between primary PCa and metastatic PCa (MPCa) samples. Then we constructed the MPCa-specific microRNA-mRNA network and screened microRNA biomarkers by a novel bioinformatics model. The model emphasized the characterization of systems stability changes and the network vulnerability with three measurements, i.e. the structurally single-line regulation, the functional importance of microRNA targets and the percentage of transcription factor genes in microRNA unique targets. With this model, we identified five microRNAs as putative biomarkers for PCa metastasis. Among them, miR-101-3p and miR-145-5p have been previously reported as biomarkers for PCa metastasis and the remaining three, i.e. miR-204-5p, miR-198 and miR-152, were screened as novel biomarkers for PCa metastasis. The results were further confirmed by the assessment of their predictive power and biological function analysis. Five microRNAs were identified as candidate biomarkers for predicting PCa metastasis based on our network vulnerability analysis model. The prediction performance, literature exploration and functional enrichment analysis convinced our findings. This novel bioinformatics model could be applied to biomarker discovery for other complex diseases.

Lycopene and Risk of Prostate Cancer

PubMed Central

Chen, Ping; Zhang, Wenhao; Wang, Xiao; Zhao, Keke; Negi, Devendra Singh; Zhuo, Li; Qi, Mao; Wang, Xinghuan; Zhang, Xinhua

2015-01-01

Abstract Prostate cancer (PCa) is a common illness for aging males. Lycopene has been identified as an antioxidant agent with potential anticancer properties. Studies investigating the relation between lycopene and PCa risk have produced inconsistent results. This study aims to determine dietary lycopene consumption/circulating concentration and any potential dose–response associations with the risk of PCa. Eligible studies published in English up to April 10, 2014, were searched and identified from Pubmed, Sciencedirect Online, Wiley online library databases and hand searching. The STATA (version 12.0) was applied to process the dose–response meta-analysis. Random effects models were used to calculate pooled relative risks (RRs) and 95% confidence intervals (CIs) and to incorporate variation between studies. The linear and nonlinear dose–response relations were evaluated with data from categories of lycopene consumption/circulating concentrations. Twenty-six studies were included with 17,517 cases of PCa reported from 563,299 participants. Although inverse association between lycopene consumption and PCa risk was not found in all studies, there was a trend that with higher lycopene intake, there was reduced incidence of PCa (P = 0.078). Removal of one Chinese study in sensitivity analysis, or recalculation using data from only high-quality studies for subgroup analysis, indicated that higher lycopene consumption significantly lowered PCa risk. Furthermore, our dose–response meta-analysis demonstrated that higher lycopene consumption was linearly associated with a reduced risk of PCa with a threshold between 9 and 21 mg/day. Consistently, higher circulating lycopene levels significantly reduced the risk of PCa. Interestingly, the concentration of circulating lycopene between 2.17 and 85 μg/dL was linearly inversed with PCa risk whereas there was no linear association >85 μg/dL. In addition, greater efficacy for the circulating lycopene concentration on preventing PCa was found for studies with high quality, follow-up >10 years and where results were adjusted by the age or the body mass index. In conclusion, our novel data demonstrates that higher lycopene consumption/circulating concentration is associated with a lower risk of PCa. However, further studies are required to determine the mechanism by which lycopene reduces the risk of PCa and if there are other factors in tomato products that might potentially decrease PCa risk and progression. PMID:26287411

Stability of Nonlinear Principal Components Analysis: An Empirical Study Using the Balanced Bootstrap

ERIC Educational Resources Information Center

Linting, Marielle; Meulman, Jacqueline J.; Groenen, Patrick J. F.; van der Kooij, Anita J.

2007-01-01

Principal components analysis (PCA) is used to explore the structure of data sets containing linearly related numeric variables. Alternatively, nonlinear PCA can handle possibly nonlinearly related numeric as well as nonnumeric variables. For linear PCA, the stability of its solution can be established under the assumption of multivariate…

DWI-associated entire-tumor histogram analysis for the differentiation of low-grade prostate cancer from intermediate-high-grade prostate cancer.

PubMed

Wu, Chen-Jiang; Wang, Qing; Li, Hai; Wang, Xiao-Ning; Liu, Xi-Sheng; Shi, Hai-Bin; Zhang, Yu-Dong

2015-10-01

To investigate diagnostic efficiency of DWI using entire-tumor histogram analysis in differentiating the low-grade (LG) prostate cancer (PCa) from intermediate-high-grade (HG) PCa in comparison with conventional ROI-based measurement. DW images (b of 0-1400 s/mm(2)) from 126 pathology-confirmed PCa (diameter >0.5 cm) in 110 patients were retrospectively collected and processed by mono-exponential model. The measurement of tumor apparent diffusion coefficients (ADCs) was performed with using histogram-based and ROI-based approach, respectively. The diagnostic ability of ADCs from two methods for differentiating LG-PCa (Gleason score, GS ≤ 6) from HG-PCa (GS > 6) was determined by ROC regression, and compared by McNemar's test. There were 49 LG-tumor and 77 HG-tumor at pathologic findings. Histogram-based ADCs (mean, median, 10th and 90th) and ROI-based ADCs (mean) showed dominant relationships with ordinal GS of Pca (ρ = -0.225 to -0.406, p < 0.05). All above imaging indices reflected significant difference between LG-PCa and HG-PCa (all p values <0.01). Histogram 10th ADCs had dominantly high Az (0.738), Youden index (0.415), and positive likelihood ratio (LR+, 2.45) in stratifying tumor GS against mean, median and 90th ADCs, and ROI-based ADCs. Histogram mean, median, and 10th ADCs showed higher specificity (65.3%-74.1% vs. 44.9%, p < 0.01), but lower sensitivity (57.1%-71.3% vs. 84.4%, p < 0.05) than ROI-based ADCs in differentiating LG-PCa from HG-PCa. DWI-associated histogram analysis had higher specificity, Az, Youden index, and LR+ for differentiation of PCa Gleason grade than ROI-based approach.

Performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches in VQ codebook generation for image compression

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Chou, Ping-Yi; Chou, Jyh-Horng

2015-11-01

The aim of this study is to generate vector quantisation (VQ) codebooks by integrating principle component analysis (PCA) algorithm, Linde-Buzo-Gray (LBG) algorithm, and evolutionary algorithms (EAs). The EAs include genetic algorithm (GA), particle swarm optimisation (PSO), honey bee mating optimisation (HBMO), and firefly algorithm (FF). The study is to provide performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches. The PCA-EA-LBG approaches contain PCA-GA-LBG, PCA-PSO-LBG, PCA-HBMO-LBG, and PCA-FF-LBG, while the PCA-LBG-EA approaches contain PCA-LBG, PCA-LBG-GA, PCA-LBG-PSO, PCA-LBG-HBMO, and PCA-LBG-FF. All training vectors of test images are grouped according to PCA. The PCA-EA-LBG used the vectors grouped by PCA as initial individuals, and the best solution gained by the EAs was given for LBG to discover a codebook. The PCA-LBG approach is to use the PCA to select vectors as initial individuals for LBG to find a codebook. The PCA-LBG-EA used the final result of PCA-LBG as an initial individual for EAs to find a codebook. The search schemes in PCA-EA-LBG first used global search and then applied local search skill, while in PCA-LBG-EA first used local search and then employed global search skill. The results verify that the PCA-EA-LBG indeed gain superior results compared to the PCA-LBG-EA, because the PCA-EA-LBG explores a global area to find a solution, and then exploits a better one from the local area of the solution. Furthermore the proposed PCA-EA-LBG approaches in designing VQ codebooks outperform existing approaches shown in the literature.

Machine learning-based analysis of MR radiomics can help to improve the diagnostic performance of PI-RADS v2 in clinically relevant prostate cancer.

PubMed

Wang, Jing; Wu, Chen-Jiang; Bao, Mei-Ling; Zhang, Jing; Wang, Xiao-Ning; Zhang, Yu-Dong

2017-10-01

To investigate whether machine learning-based analysis of MR radiomics can help improve the performance PI-RADS v2 in clinically relevant prostate cancer (PCa). This IRB-approved study included 54 patients with PCa undergoing multi-parametric (mp) MRI before prostatectomy. Imaging analysis was performed on 54 tumours, 47 normal peripheral (PZ) and 48 normal transitional (TZ) zone based on histological-radiological correlation. Mp-MRI was scored via PI-RADS, and quantified by measuring radiomic features. Predictive model was developed using a novel support vector machine trained with: (i) radiomics, (ii) PI-RADS scores, (iii) radiomics and PI-RADS scores. Paired comparison was made via ROC analysis. For PCa versus normal TZ, the model trained with radiomics had a significantly higher area under the ROC curve (Az) (0.955 [95% CI 0.923-0.976]) than PI-RADS (Az: 0.878 [0.834-0.914], p < 0.001). The Az between them was insignificant for PCa versus PZ (0.972 [0.945-0.988] vs. 0.940 [0.905-0.965], p = 0.097). When radiomics was added, performance of PI-RADS was significantly improved for PCa versus PZ (Az: 0.983 [0.960-0.995]) and PCa versus TZ (Az: 0.968 [0.940-0.985]). Machine learning analysis of MR radiomics can help improve the performance of PI-RADS in clinically relevant PCa. • Machine-based analysis of MR radiomics outperformed in TZ cancer against PI-RADS. • Adding MR radiomics significantly improved the performance of PI-RADS. • DKI-derived Dapp and Kapp were two strong markers for the diagnosis of PCa.

Applying robust variant of Principal Component Analysis as a damage detector in the presence of outliers

NASA Astrophysics Data System (ADS)

Gharibnezhad, Fahit; Mujica, Luis E.; Rodellar, José

2015-01-01

Using Principal Component Analysis (PCA) for Structural Health Monitoring (SHM) has received considerable attention over the past few years. PCA has been used not only as a direct method to identify, classify and localize damages but also as a significant primary step for other methods. Despite several positive specifications that PCA conveys, it is very sensitive to outliers. Outliers are anomalous observations that can affect the variance and the covariance as vital parts of PCA method. Therefore, the results based on PCA in the presence of outliers are not fully satisfactory. As a main contribution, this work suggests the use of robust variant of PCA not sensitive to outliers, as an effective way to deal with this problem in SHM field. In addition, the robust PCA is compared with the classical PCA in the sense of detecting probable damages. The comparison between the results shows that robust PCA can distinguish the damages much better than using classical one, and even in many cases allows the detection where classic PCA is not able to discern between damaged and non-damaged structures. Moreover, different types of robust PCA are compared with each other as well as with classical counterpart in the term of damage detection. All the results are obtained through experiments with an aircraft turbine blade using piezoelectric transducers as sensors and actuators and adding simulated damages.

Genomic and epigenomic analysis of high-risk prostate cancer reveals changes in hydroxymethylation and TET1.

PubMed

Spans, Lien; Van den Broeck, Thomas; Smeets, Elien; Prekovic, Stefan; Thienpont, Bernard; Lambrechts, Diether; Karnes, R Jeffrey; Erho, Nicholas; Alshalalfa, Mohammed; Davicioni, Elai; Helsen, Christine; Gevaert, Thomas; Tosco, Lorenzo; Haustermans, Karin; Lerut, Evelyne; Joniau, Steven; Claessens, Frank

2016-04-26

The clinical heterogeneity of prostate cancer (PCa) makes it difficult to identify those patients that could benefit from more aggressive treatments. As a contribution to a better understanding of the genomic changes in the primary tumor that are associated with the development of high-risk disease, we performed exome sequencing and copy number determination of a clinically homogeneous cohort of 47 high-risk PCas. We confirmed recurrent mutations in SPOP, PTEN and TP53 among the 850 point mutations we detected. In seven cases, we discovered genomic aberrations in the TET1 (Ten-Eleven Translocation 1) gene which encodes a DNA hydroxymethylase than can modify methylated cytosines in genomic DNA and thus is linked with gene expression changes. TET1 protein levels were reduced in tumor versus non-tumor prostate tissue in 39 of 40 cases. The clinical relevance of changes in TET1 levels was demonstrated in an independent PCa cohort, in which low TET1 mRNA levels were significantly associated with worse metastases-free survival. We also demonstrate a strong reduction in hydroxymethylated DNA in tumor tissue in 27 of 41 cases. Furthermore, we report the first exploratory (h)MeDIP-Seq analyses of eight high-risk PCa samples. This reveals a large heterogeneity in hydroxymethylation changes in tumor versus non-tumor genomes which can be linked with cell polarity.

Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA) wastewater data.

PubMed

Salvatore, Stefania; Bramness, Jørgen G; Røislien, Jo

2016-07-12

Wastewater-based epidemiology (WBE) is a novel approach in drug use epidemiology which aims to monitor the extent of use of various drugs in a community. In this study, we investigate functional principal component analysis (FPCA) as a tool for analysing WBE data and compare it to traditional principal component analysis (PCA) and to wavelet principal component analysis (WPCA) which is more flexible temporally. We analysed temporal wastewater data from 42 European cities collected daily over one week in March 2013. The main temporal features of ecstasy (MDMA) were extracted using FPCA using both Fourier and B-spline basis functions with three different smoothing parameters, along with PCA and WPCA with different mother wavelets and shrinkage rules. The stability of FPCA was explored through bootstrapping and analysis of sensitivity to missing data. The first three principal components (PCs), functional principal components (FPCs) and wavelet principal components (WPCs) explained 87.5-99.6 % of the temporal variation between cities, depending on the choice of basis and smoothing. The extracted temporal features from PCA, FPCA and WPCA were consistent. FPCA using Fourier basis and common-optimal smoothing was the most stable and least sensitive to missing data. FPCA is a flexible and analytically tractable method for analysing temporal changes in wastewater data, and is robust to missing data. WPCA did not reveal any rapid temporal changes in the data not captured by FPCA. Overall the results suggest FPCA with Fourier basis functions and common-optimal smoothing parameter as the most accurate approach when analysing WBE data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Das, Dibash K.; The Graduate Center Departments of Biology and Biochemistry, The City University of New York, New York, NY 10016; Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY 10065

Prostate cancer (PCa) is frequently diagnosed in men, and dysregulation of microRNAs is characteristic of many cancers. MicroRNA-1207-3p is encoded at the non-protein coding gene locus PVT1 on the 8q24 human chromosomal region, an established PCa susceptibility locus. However, the role of microRNA-1207-3p in PCa is unclear. We discovered that microRNA-1207-3p is significantly underexpressed in PCa cell lines in comparison to normal prostate epithelial cells. Increased expression of microRNA-1207-3p in PCa cells significantly inhibits proliferation, migration, and induces apoptosis via direct molecular targeting of FNDC1, a protein which contains a conserved protein domain of fibronectin (FN1). FNDC1, FN1, and themore » androgen receptor (AR) are significantly overexpressed in PCa cell lines and human PCa, and positively correlate with aggressive PCa. Prostate tumor FN1 expression in patients that experienced PCa-specific death is significantly higher than in patients that remained alive. Furthermore, FNDC1, FN1 and AR are concomitantly overexpressed in metastatic PCa. Consequently, these studies have revealed a novel microRNA-1207-3p/FNDC1/FN1/AR regulatory pathway in PCa. - Graphical abstract: miR-1207-3p/FNDC1/FN1/AR is a novel regulatory pathway in prostate cancer. - Highlights: • Expression of microRNA-1207-3p is significantly lost in prostate cancer (PCa) cells. • MicroRNA-1207-3p regulates proliferation, apoptosis, and migration via direct molecular targeting of the 3′UTR of FNDC1. • MicroRNA-1207-3p regulates proliferation, apoptosis, and migration via direct molecular targeting of the 3′UTR of FNDC1. • FNDC1, FN1, and AR are concurrently overexpressed in metastatic PCa.« less

EFEMP1 as a novel DNA methylation marker for prostate cancer: array-based DNA methylation and expression profiling.

PubMed

Kim, Yong-June; Yoon, Hyung-Yoon; Kim, Seon-Kyu; Kim, Young-Won; Kim, Eun-Jung; Kim, Isaac Yi; Kim, Wun-Jae

2011-07-01

Abnormal DNA methylation is associated with many human cancers. The aim of the present study was to identify novel methylation markers in prostate cancer (PCa) by microarray analysis and to test whether these markers could discriminate normal and PCa cells. Microarray-based DNA methylation and gene expression profiling was carried out using a panel of PCa cell lines and a control normal prostate cell line. The methylation status of candidate genes in prostate cell lines was confirmed by real-time reverse transcriptase-PCR, bisulfite sequencing analysis, and treatment with a demethylation agent. DNA methylation and gene expression analysis in 203 human prostate specimens, including 106 PCa and 97 benign prostate hyperplasia (BPH), were carried out. Further validation using microarray gene expression data from the Gene Expression Omnibus (GEO) was carried out. Epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1) was identified as a lead candidate methylation marker for PCa. The gene expression level of EFEMP1 was significantly higher in tissue samples from patients with BPH than in those with PCa (P < 0.001). The sensitivity and specificity of EFEMP1 methylation status in discriminating between PCa and BPH reached 95.3% (101 of 106) and 86.6% (84 of 97), respectively. From the GEO data set, we confirmed that the expression level of EFEMP1 was significantly different between PCa and BPH. Genome-wide characterization of DNA methylation profiles enabled the identification of EFEMP1 aberrant methylation patterns in PCa. EFEMP1 might be a useful indicator for the detection of PCa.

Racial disparities: disruptive genes in prostate carcinogenesis.

PubMed

Singh, Savita; Plaga, Alexis; Shukla, Girish C

2017-06-01

Population specific studies in prostate cancer (PCa) reveal a unique heterogeneous etiology. Various factors, such as genetics, environment and dietary regimen seems to determine disease progression, therapeutic resistance and rate of mortality. Enormous disparity documented in disease incidences, aggressiveness and mortality in PCa among AAs (African Americans) and CAs (Caucasian Americans) is attributed to the variations in genetics, epigenetics and their association with metabolism. Scientific and clinical evidences have revealed the influence of variations in Androgen Receptor (AR), RNAse L, macrophage scavenger receptor 1 ( MRS1 ), androgen metabolism by cytochrome P450 3A4, differential regulation of microRNAs, epigenetic alterations and diet in racial disparity in PCa incidences and mortality. Concerted efforts are needed to identify race specific prognostic markers and treatment regimen for a better management of the disease.

Using Serological Proteome Analysis to Identify Serum Anti-Nucleophosmin 1 Autoantibody as a Potential Biomarker in European-American and African-American Patients With Prostate Cancer.

PubMed

Dai, Liping; Li, Jitian; Xing, Mengtao; Sanchez, Tino W; Casiano, Carlos A; Zhang, Jian-Ying

2016-11-01

The prostate-specific antigen (PSA) testing has been widely implemented for the early detection and management of prostate cancer (PCa). However, the lack of specificity has led to overdiagnosis, resulting in many possibly unnecessary biopsies and overtreatment. Therefore, novel serological biomarkers with high sensitivity and specificity are of vital importance needed to complement PSA testing in the early diagnosis and effective management of PCa. This is particularly critical in the context of PCa health disparities, where early detection and management could help reduce the disproportionately high PCa mortality observed in African-American men. Previous studies have demonstrated that sera from patients with PCa contain autoantibodies that react with tumor-associated antigens (TAAs). The serological proteome analysis (SERPA) approach was used to identify tumor-associated antigens (TAAs) of PCa. In evaluation study, the level of anti-NPM1 antibody was examined in sera from test cohort, validation cohort, as well as European-American (EA) and African-American (AA) men with PCa by using immunoassay. Nucleophosmin 1 (NPM1) as a 33 kDa TAA in PCa was identified and characterized by SERPA approach. Anti-NPM1 antibody level in PCa was higher than in benign prostatic hyperplasia (BPH) patients and healthy individuals. Receiver operating characteristic (ROC) curve analysis showed similar high diagnostic value for PCa in the test cohort (area under the curve (AUC):0.860) and validation cohort (AUC: 0.822) to differentiate from normal individuals and BPH. Interestingly, AUC values were significantly higher for AA PCa patients. When considering concurrent serum measurements of anti-NPM1 antibody and PSA, 97.1% PCa patients at early stage were identified correctly, while 69.2% BPH patients who had elevated PSA levels were found to be anti-NPM1 negative. Additionally, anti-NPM1 antibody levels in PCa patients at early stage significantly increased after surgery treatment. This intriguing data suggested that NPM1 can elicit autoantibody response in PCa and might be a potential biomarker for the immunodiagnosis and prognosis of PCa, and for supplementing PSA testing in distinguishing PCa from BPH. Prostate 76:1375-1386, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Correlation between doctor's belief on the patient's self-determination and medical outcomes in obtaining informed consent.

PubMed

Yoshihara, Keisuke; Takase, Kozo

2013-03-01

We employed a questionnaire survey to assess attitudes toward informed consent (IC) among hospital doctors. Based on the result of the correlation analysis, the following two hypotheses were identified. The first hypothesis is that "the doctor's belief that the patient's self-determination is possible promotes cure of illness by obtaining IC." The second hypothesis is that "the doctor's belief that the patient's self-determination is possible has a positive influence on patient's quality of life by obtaining IC." We clarified the rationale for explaining these two hypotheses by applying cross tabulation analysis, discriminant analysis and principal component analysis (PCA). The doctors were divided into two groups in terms of their position on the patient's self-determination. One group of doctors believed the possibility of patient's self-determination, and the other did not. Through our statistical analyses, the characteristics that discriminate these two groups were identified. It was revealed that the former group placed a great importance on the hospitality value, while the latter placed an importance on the service value. Agreement or rejection of the concept of IC has been demonstrated as a key distinguishing factor between the two groups. The results of PCA showed that the doctor's belief on the patient's self-determination in obtaining IC had a significant effect on medical outcomes, and the two above-mentioned hypotheses were revealed.

Systematic study of anharmonic features in a principal component analysis of gramicidin A.

PubMed

Kurylowicz, Martin; Yu, Ching-Hsing; Pomès, Régis

2010-02-03

We use principal component analysis (PCA) to detect functionally interesting collective motions in molecular-dynamics simulations of membrane-bound gramicidin A. We examine the statistical and structural properties of all PCA eigenvectors and eigenvalues for the backbone and side-chain atoms. All eigenvalue spectra show two distinct power-law scaling regimes, quantitatively separating large from small covariance motions. Time trajectories of the largest PCs converge to Gaussian distributions at long timescales, but groups of small-covariance PCs, which are usually ignored as noise, have subdiffusive distributions. These non-Gaussian distributions imply anharmonic motions on the free-energy surface. We characterize the anharmonic components of motion by analyzing the mean-square displacement for all PCs. The subdiffusive components reveal picosecond-scale oscillations in the mean-square displacement at frequencies consistent with infrared measurements. In this regime, the slowest backbone mode exhibits tilting of the peptide planes, which allows carbonyl oxygen atoms to provide surrogate solvation for water and cation transport in the channel lumen. Higher-frequency modes are also apparent, and we describe their vibrational spectra. Our findings expand the utility of PCA for quantifying the essential features of motion on the anharmonic free-energy surface made accessible by atomistic molecular-dynamics simulations. Copyright (c) 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Enhanced expression of SRPK2 contributes to aggressive progression and metastasis in prostate cancer.

PubMed

Zhuo, Yang Jia; Liu, Ze Zhen; Wan, Song; Cai, Zhi Duan; Xie, Jian Jiang; Cai, Zhou da; Song, Sheng da; Wan, Yue Ping; Hua, Wei; Zhong, Wei de; Wu, Chin Lee

2018-06-01

Serine/Arginine-Rich Protein-Specific Kinase-2 (SRSF protein kinase-2, SRPK2) is up-regulated in multiple human tumors. However, the expression, function and clinical significance of SRPK2 in prostate cancer (PCa) has not yet been understood. We therefore aimed to determine the association of SRPK2 with tumor progression and metastasis in PCa patients in our present study. The expression of SRPK2 was detected by some public datasets and validated using a clinical tissue microarray (TMA) by immunohistochemistry. The association of SRPK2 expression with various clinicopathological characteristics of PCa patients was subsequently statistically analyzed based on the The Cancer Genome Atlas (TCGA) dataset and clinical TMA. The effects of SRPK2 on cancer cell proliferation, migration, invasion, cell cycle progression, apoptosis and tumor growth were then respectively investigated using in vitro and in vivo experiments. First, public datasets showed that SRPK2 expression was greater in PCa tissues when compared with non-cancerous tissues. Statistical analysis demonstrated that high expression of SRPK2 was significantly correlated with a higher Gleason Score, advanced pathological stage and the presence of tumor metastasis in the TCGA Dataset (all P < 0.01). Similar correlations between SRPK2 and a higher Gleason Score or advanced pathological stage were also identified in the TMA (P < 0.05). Kaplan-Meier curve analyses showed that the biochemical recurrence (BCR)-free time of PCa patients with SRPK2 high expression was shorter than for those with SRPK2 low expression (P < 0.05). Second, cell function experiments in PCa cell lines revealed that enhanced SRPK2 expression could promote cell proliferation, migration, invasion and cell cycle progression but suppress tumor cell apoptosis in vitro. Xenograft experiments showed that SRPK2 promoted tumor growth in vivo. In conclusion, our data demonstrated that SRPK2 may play an important role in the progression and metastasis of PCa, which suggests that it might be a potential therapeutic target for PCa clinical therapy. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Metabolomics and transcriptomics profiles reveal the dysregulation of the tricarboxylic acid cycle and related mechanisms in prostate cancer.

PubMed

Shao, Yaping; Ye, Guozhu; Ren, Shancheng; Piao, Hai-Long; Zhao, Xinjie; Lu, Xin; Wang, Fubo; Ma, Wang; Li, Jia; Yin, Peiyuan; Xia, Tian; Xu, Chuanliang; Yu, Jane J; Sun, Yinghao; Xu, Guowang

2018-07-15

Genetic alterations drive metabolic reprograming to meet increased biosynthetic precursor and energy demands for cancer cell proliferation and survival in unfavorable environments. A systematic study of gene-metabolite regulatory networks and metabolic dysregulation should reveal the molecular mechanisms underlying prostate cancer (PCa) pathogenesis. Herein, we performed gas chromatography-mass spectrometry (GC-MS)-based metabolomics and RNA-seq analyses in prostate tumors and matched adjacent normal tissues (ANTs) to elucidate the molecular alterations and potential underlying regulatory mechanisms in PCa. Significant accumulation of metabolic intermediates and enrichment of genes in the tricarboxylic acid (TCA) cycle were observed in tumor tissues, indicating TCA cycle hyperactivation in PCa tissues. In addition, the levels of fumarate and malate were highly correlated with the Gleason score, tumor stage and expression of genes encoding related enzymes and were significantly related to the expression of genes involved in branched chain amino acid degradation. Using an integrated omics approach, we further revealed the potential anaplerotic routes from pyruvate, glutamine catabolism and branched chain amino acid (BCAA) degradation contributing to replenishing metabolites for TCA cycle. Integrated omics techniques enable the performance of network-based analyses to gain a comprehensive and in-depth understanding of PCa pathophysiology and may facilitate the development of new and effective therapeutic strategies. © 2018 UICC.

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge

PubMed Central

Wagner, Florian

2015-01-01

Method Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. Results I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets. PMID:26575370

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge.

PubMed

Wagner, Florian

2015-01-01

Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets.

Incorporating biological information in sparse principal component analysis with application to genomic data.

PubMed

Li, Ziyi; Safo, Sandra E; Long, Qi

2017-07-11

Sparse principal component analysis (PCA) is a popular tool for dimensionality reduction, pattern recognition, and visualization of high dimensional data. It has been recognized that complex biological mechanisms occur through concerted relationships of multiple genes working in networks that are often represented by graphs. Recent work has shown that incorporating such biological information improves feature selection and prediction performance in regression analysis, but there has been limited work on extending this approach to PCA. In this article, we propose two new sparse PCA methods called Fused and Grouped sparse PCA that enable incorporation of prior biological information in variable selection. Our simulation studies suggest that, compared to existing sparse PCA methods, the proposed methods achieve higher sensitivity and specificity when the graph structure is correctly specified, and are fairly robust to misspecified graph structures. Application to a glioblastoma gene expression dataset identified pathways that are suggested in the literature to be related with glioblastoma. The proposed sparse PCA methods Fused and Grouped sparse PCA can effectively incorporate prior biological information in variable selection, leading to improved feature selection and more interpretable principal component loadings and potentially providing insights on molecular underpinnings of complex diseases.

DNA methylome changes by estradiol benzoate and bisphenol A links early-life environmental exposures to prostate cancer risk

PubMed Central

Cheong, Ana; Zhang, Xiang; Cheung, Yuk-Yin; Tang, Wan-yee; Chen, Jing; Ye, Shu-Hua; Medvedovic, Mario; Leung, Yuet-Kin; Prins, Gail S.; Ho, Shuk-Mei

2016-01-01

ABSTRACT Developmental exposure to endocrine-disrupting chemicals (EDCs), 17β-estradiol-3-benzoate (EB) and bisphenol A (BPA), increases susceptibility to prostate cancer (PCa) in rodent models. Here, we used the methylated-CpG island recovery assay (MIRA)-assisted genomic tiling and CpG island arrays to identify treatment-associated methylome changes in the postnatal day (PND)90 dorsal prostate tissues of Sprague-Dawley rats neonatally (PND1, 3, and 5) treated with 25 µg/pup or 2,500 µg EB/kg body weight (BW) or 0.1 µg BPA/pup or 10 µg BPA/kg BW. We identified 111 EB-associated and 86 BPA-associated genes, with 20 in common, that have significant differentially methylated regions. Pathway analysis revealed cancer as the top common disease pathway. Bisulfite sequencing validated the differential methylation patterns observed by array analysis in 15 identified candidate genes. The methylation status of 7 (Pitx3, Wnt10b, Paqr4, Sox2, Chst14, Tpd52, Creb3l4) of these 15 genes exhibited an inverse correlation with gene expression in tissue samples. Cell-based assays, using 5-aza-cytidine-treated normal (NbE-1) and cancerous (AIT) rat prostate cells, added evidence of DNA methylation-mediated gene expression of 6 genes (exception: Paqr4). Functional connectivity of these genes was linked to embryonic stem cell pluripotency. Furthermore, clustering analyses using the dataset from The Cancer Genome Atlas revealed that expression of this set of 7 genes was associated with recurrence-free survival of PCa patients. In conclusion, our study reveals that gene-specific promoter methylation changes, resulting from early-life EDC exposure in the rat, may serve as predictive epigenetic biomarkers of PCa recurrence, and raises the possibility that such exposure may impact human disease. PMID:27415467

DNA methylome changes by estradiol benzoate and bisphenol A links early-life environmental exposures to prostate cancer risk.

PubMed

Cheong, Ana; Zhang, Xiang; Cheung, Yuk-Yin; Tang, Wan-Yee; Chen, Jing; Ye, Shu-Hua; Medvedovic, Mario; Leung, Yuet-Kin; Prins, Gail S; Ho, Shuk-Mei

2016-09-01

Developmental exposure to endocrine-disrupting chemicals (EDCs), 17β-estradiol-3-benzoate (EB) and bisphenol A (BPA), increases susceptibility to prostate cancer (PCa) in rodent models. Here, we used the methylated-CpG island recovery assay (MIRA)-assisted genomic tiling and CpG island arrays to identify treatment-associated methylome changes in the postnatal day (PND)90 dorsal prostate tissues of Sprague-Dawley rats neonatally (PND1, 3, and 5) treated with 25 µg/pup or 2,500 µg EB/kg body weight (BW) or 0.1 µg BPA/pup or 10 µg BPA/kg BW. We identified 111 EB-associated and 86 BPA-associated genes, with 20 in common, that have significant differentially methylated regions. Pathway analysis revealed cancer as the top common disease pathway. Bisulfite sequencing validated the differential methylation patterns observed by array analysis in 15 identified candidate genes. The methylation status of 7 (Pitx3, Wnt10b, Paqr4, Sox2, Chst14, Tpd52, Creb3l4) of these 15 genes exhibited an inverse correlation with gene expression in tissue samples. Cell-based assays, using 5-aza-cytidine-treated normal (NbE-1) and cancerous (AIT) rat prostate cells, added evidence of DNA methylation-mediated gene expression of 6 genes (exception: Paqr4). Functional connectivity of these genes was linked to embryonic stem cell pluripotency. Furthermore, clustering analyses using the dataset from The Cancer Genome Atlas revealed that expression of this set of 7 genes was associated with recurrence-free survival of PCa patients. In conclusion, our study reveals that gene-specific promoter methylation changes, resulting from early-life EDC exposure in the rat, may serve as predictive epigenetic biomarkers of PCa recurrence, and raises the possibility that such exposure may impact human disease.

Problematic mobile phone use in adolescents: derivation of a short scale MPPUS-10.

PubMed

Foerster, Milena; Roser, Katharina; Schoeni, Anna; Röösli, Martin

2015-02-01

Our aim was to derive a short version of the Mobile Phone Problem Use Scale (MPPUS) using data from 412 adolescents of the Swiss HERMES (Health Effects Related to Mobile phonE use in adolescentS) cohort. A German version of the original MPPUS consisting of 27 items was shortened by principal component analysis (PCA) using baseline data collected in 2012. For confirmation, the PCA was carried out again with follow-up data 1 year later. PCA revealed four factors related to symptoms of addiction (Loss of Control, Withdrawal, Negative Life Consequences and Craving) and a fifth factor reflecting the social component of mobile phone use (Peer Dependence). The shortened scale (MPPUS-10) highly reflects the original MPPUS (Kendalls' Tau: 0.80 with 90% concordant pairs). Internal consistency of MPPUS-10 was good with Cronbach's alpha: 0.85. The results were confirmed using the follow-up data. The MPPUS-10 is a suitable instrument for research in adolescents. It will help to further clarify the definition of problematic mobile phone use in adolescents and explore similarities and differences to other technological addictions.

Distinguishing ovarian maturity of farmed white sturgeon (Acipenser transmontanus) by Fourier transform infrared spectroscopy: a potential tool for caviar production management.

PubMed

Lu, Xiaonan; Webb, Molly; Talbott, Mariah; Van Eenennaam, Joel; Palumbo, Amanda; Linares-Casenave, Javier; Doroshov, Serge; Struffenegger, Peter; Rasco, Barbara

2010-04-14

Fourier transform infrared spectroscopy (FT-IR, 4000-400 cm(-1)) was applied to blood plasma of farmed white sturgeon (N = 40) to differentiate and predict the stages of ovarian maturity. Spectral features of sex steroids (approximately 3000 cm(-1)) and vitellogenin (approximately 1080 cm(-1)) were identified. Clear segregation of maturity stages (previtellogenesis, vitellogenesis, postvitellogenesis, and follicular atresia) was achieved using principal component analysis (PCA). Progression of oocyte development in the late phase of vitellogenesis was also monitored using PCA based on changes in plasma concentrations of sex steroid and lipid content. The observed oocyte polarization index (PI, a measure of nuclear migration) was correlated with changes in plasma sex steroid levels revealed by FT-IR PCA results. A partial least squares (PLS) model predicted PI values within the range 0.12-0.40 (R = 0.95, SEP = 2.18%) from differences in spectral features. These results suggest that FT-IR may be a good tool for assessing ovarian maturity in farmed sturgeon and will reduce the need for the invasive ovarian biopsy required for PI determination.

Investigation of probabilistic principal component analysis compared to proper orthogonal decomposition methods for basis extraction and missing data estimation

NASA Astrophysics Data System (ADS)

Lee, Kyunghoon

To evaluate the maximum likelihood estimates (MLEs) of probabilistic principal component analysis (PPCA) parameters such as a factor-loading, PPCA can invoke an expectation-maximization (EM) algorithm, yielding an EM algorithm for PPCA (EM-PCA). In order to examine the benefits of the EM-PCA for aerospace engineering applications, this thesis attempts to qualitatively and quantitatively scrutinize the EM-PCA alongside both POD and gappy POD using high-dimensional simulation data. In pursuing qualitative investigations, the theoretical relationship between POD and PPCA is transparent such that the factor-loading MLE of PPCA, evaluated by the EM-PCA, pertains to an orthogonal basis obtained by POD. By contrast, the analytical connection between gappy POD and the EM-PCA is nebulous because they distinctively approximate missing data due to their antithetical formulation perspectives: gappy POD solves a least-squares problem whereas the EM-PCA relies on the expectation of the observation probability model. To juxtapose both gappy POD and the EM-PCA, this research proposes a unifying least-squares perspective that embraces the two disparate algorithms within a generalized least-squares framework. As a result, the unifying perspective reveals that both methods address similar least-squares problems; however, their formulations contain dissimilar bases and norms. Furthermore, this research delves into the ramifications of the different bases and norms that will eventually characterize the traits of both methods. To this end, two hybrid algorithms of gappy POD and the EM-PCA are devised and compared to the original algorithms for a qualitative illustration of the different basis and norm effects. After all, a norm reflecting a curve-fitting method is found to more significantly affect estimation error reduction than a basis for two example test data sets: one is absent of data only at a single snapshot and the other misses data across all the snapshots. From a numerical performance aspect, the EM-PCA is computationally less efficient than POD for intact data since it suffers from slow convergence inherited from the EM algorithm. For incomplete data, this thesis quantitatively found that the number of data missing snapshots predetermines whether the EM-PCA or gappy POD outperforms the other because of the computational cost of a coefficient evaluation, resulting from a norm selection. For instance, gappy POD demands laborious computational effort in proportion to the number of data-missing snapshots as a consequence of the gappy norm. In contrast, the computational cost of the EM-PCA is invariant to the number of data-missing snapshots thanks to the L2 norm. In general, the higher the number of data-missing snapshots, the wider the gap between the computational cost of gappy POD and the EM-PCA. Based on the numerical experiments reported in this thesis, the following criterion is recommended regarding the selection between gappy POD and the EM-PCA for computational efficiency: gappy POD for an incomplete data set containing a few data-missing snapshots and the EM-PCA for an incomplete data set involving multiple data-missing snapshots. Last, the EM-PCA is applied to two aerospace applications in comparison to gappy POD as a proof of concept: one with an emphasis on basis extraction and the other with a focus on missing data reconstruction for a given incomplete data set with scattered missing data. The first application exploits the EM-PCA to efficiently construct reduced-order models of engine deck responses obtained by the numerical propulsion system simulation (NPSS), some of whose results are absent due to failed analyses caused by numerical instability. Model-prediction tests validate that engine performance metrics estimated by the reduced-order NPSS model exhibit considerably good agreement with those directly obtained by NPSS. Similarly, the second application illustrates that the EM-PCA is significantly more cost effective than gappy POD at repairing spurious PIV measurements obtained from acoustically-excited, bluff-body jet flow experiments. The EM-PCA reduces computational cost on factors 8 ˜ 19 compared to gappy POD while generating the same restoration results as those evaluated by gappy POD. All in all, through comprehensive theoretical and numerical investigation, this research establishes that the EM-PCA is an efficient alternative to gappy POD for an incomplete data set containing missing data over an entire data set. (Abstract shortened by UMI.)

Chemical information obtained from Auger depth profiles by means of advanced factor analysis (MLCFA)

NASA Astrophysics Data System (ADS)

De Volder, P.; Hoogewijs, R.; De Gryse, R.; Fiermans, L.; Vennik, J.

1993-01-01

The advanced multivariate statistical technique "maximum likelihood common factor analysis (MLCFA)" is shown to be superior to "principal component analysis (PCA)" for decomposing overlapping peaks into their individual component spectra of which neither the number of components nor the peak shape of the component spectra is known. An examination of the maximum resolving power of both techniques, MLCFA and PCA, by means of artificially created series of multicomponent spectra confirms this finding unambiguously. Substantial progress in the use of AES as a chemical-analysis technique is accomplished through the implementation of MLCFA. Chemical information from Auger depth profiles is extracted by investigating the variation of the line shape of the Auger signal as a function of the changing chemical state of the element. In particular, MLCFA combined with Auger depth profiling has been applied to problems related to steelcord-rubber tyre adhesion. MLCFA allows one to elucidate the precise nature of the interfacial layer of reaction products between natural rubber vulcanized on a thin brass layer. This study reveals many interesting chemical aspects of the oxi-sulfidation of brass undetectable with classical AES.

FPA-FTIR Microspectroscopy for Monitoring Chemotherapy Efficacy in Triple-Negative Breast Cancer

NASA Astrophysics Data System (ADS)

Zawlik, Izabela; Kaznowska, Ewa; Cebulski, Jozef; Kolodziej, Magdalena; Depciuch, Joanna; Vongsvivut, Jitraporn; Cholewa, Marian

2016-11-01

Triple-negative breast cancer is the most aggressive breast cancer subtype with limited treatment options and a poor prognosis. Approximately 70% of triple-negative breast cancer patients fail to achieve a pathologic complete response (pCR) after chemotherapy due to the lack of targeted therapies for this subtype. We report here the development of a focal-plane-array Fourier transform infrared (FPA-FTIR) microspectroscopic technique combined with principal component analysis (PCA) for monitoring chemotherapy effects in triple-negative breast cancer patients. The PCA results obtained using the FPA-FTIR spectral data collected from the same patients before and after the chemotherapy revealed discriminatory features that were consistent with the pathologic and clinical responses to chemotherapy, indicating the potential of the technique as a monitoring tool for observing chemotherapy efficacy.

Statistical Exploration of Electronic Structure of Molecules from Quantum Monte-Carlo Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prabhat, Mr; Zubarev, Dmitry; Lester, Jr., William A.

In this report, we present results from analysis of Quantum Monte Carlo (QMC) simulation data with the goal of determining internal structure of a 3N-dimensional phase space of an N-electron molecule. We are interested in mining the simulation data for patterns that might be indicative of the bond rearrangement as molecules change electronic states. We examined simulation output that tracks the positions of two coupled electrons in the singlet and triplet states of an H2 molecule. The electrons trace out a trajectory, which was analyzed with a number of statistical techniques. This project was intended to address the following scientificmore » questions: (1) Do high-dimensional phase spaces characterizing electronic structure of molecules tend to cluster in any natural way? Do we see a change in clustering patterns as we explore different electronic states of the same molecule? (2) Since it is hard to understand the high-dimensional space of trajectories, can we project these trajectories to a lower dimensional subspace to gain a better understanding of patterns? (3) Do trajectories inherently lie in a lower-dimensional manifold? Can we recover that manifold? After extensive statistical analysis, we are now in a better position to respond to these questions. (1) We definitely see clustering patterns, and differences between the H2 and H2tri datasets. These are revealed by the pamk method in a fairly reliable manner and can potentially be used to distinguish bonded and non-bonded systems and get insight into the nature of bonding. (2) Projecting to a lower dimensional subspace ({approx}4-5) using PCA or Kernel PCA reveals interesting patterns in the distribution of scalar values, which can be related to the existing descriptors of electronic structure of molecules. Also, these results can be immediately used to develop robust tools for analysis of noisy data obtained during QMC simulations (3) All dimensionality reduction and estimation techniques that we tried seem to indicate that one needs 4 or 5 components to account for most of the variance in the data, hence this 5D dataset does not necessarily lie on a well-defined, low dimensional manifold. In terms of specific clustering techniques, K-means was generally useful in exploring the dataset. The partition around medoids (pam) technique produced the most definitive results for our data showing distinctive patterns for both a sample of the complete data and time-series. The gap statistic with tibshirani criteria did not provide any distinction across the 2 dataset. The gap statistic w/DandF criteria, Model based clustering and hierarchical modeling simply failed to run on our datasets. Thankfully, the vanilla PCA technique was successful in handling our entire dataset. PCA revealed some interesting patterns for the scalar value distribution. Kernel PCA techniques (vanilladot, RBF, Polynomial) and MDS failed to run on the entire dataset, or even a significant fraction of the dataset, and we resorted to creating an explicit feature map followed by conventional PCA. Clustering using K-means and PAM in the new basis set seems to produce promising results. Understanding the new basis set in the scientific context of the problem is challenging, and we are currently working to further examine and interpret the results.« less

A feasibility study on age-related factors of wrist pulse using principal component analysis.

PubMed

Jang-Han Bae; Young Ju Jeon; Sanghun Lee; Jaeuk U Kim

2016-08-01

Various analysis methods for examining wrist pulse characteristics are needed for accurate pulse diagnosis. In this feasibility study, principal component analysis (PCA) was performed to observe age-related factors of wrist pulse from various analysis parameters. Forty subjects in the age group of 20s and 40s were participated, and their wrist pulse signal and respiration signal were acquired with the pulse tonometric device. After pre-processing of the signals, twenty analysis parameters which have been regarded as values reflecting pulse characteristics were calculated and PCA was performed. As a results, we could reduce complex parameters to lower dimension and age-related factors of wrist pulse were observed by combining-new analysis parameter derived from PCA. These results demonstrate that PCA can be useful tool for analyzing wrist pulse signal.

The impact of moderate wine consumption on the risk of developing prostate cancer.

PubMed

Vartolomei, Mihai Dorin; Kimura, Shoji; Ferro, Matteo; Foerster, Beat; Abufaraj, Mohammad; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2018-01-01

To investigate the impact of moderate wine consumption on the risk of prostate cancer (PCa). We focused on the differential effect of moderate consumption of red versus white wine. This study was a meta-analysis that includes data from case-control and cohort studies. A systematic search of Web of Science, Medline/PubMed, and Cochrane library was performed on December 1, 2017. Studies were deemed eligible if they assessed the risk of PCa due to red, white, or any wine using multivariable logistic regression analysis. We performed a formal meta-analysis for the risk of PCa according to moderate wine and wine type consumption (white or red). Heterogeneity between studies was assessed using Cochrane's Q test and I 2 statistics. Publication bias was assessed using Egger's regression test. A total of 930 abstracts and titles were initially identified. After removal of duplicates, reviews, and conference abstracts, 83 full-text original articles were screened. Seventeen studies (611,169 subjects) were included for final evaluation and fulfilled the inclusion criteria. In the case of moderate wine consumption: the pooled risk ratio (RR) for the risk of PCa was 0.98 (95% CI 0.92-1.05, p =0.57) in the multivariable analysis. Moderate white wine consumption increased the risk of PCa with a pooled RR of 1.26 (95% CI 1.10-1.43, p =0.001) in the multi-variable analysis. Meanwhile, moderate red wine consumption had a protective role reducing the risk by 12% (RR 0.88, 95% CI 0.78-0.999, p =0.047) in the multivariable analysis that comprised 222,447 subjects. In this meta-analysis, moderate wine consumption did not impact the risk of PCa. Interestingly, regarding the type of wine, moderate consumption of white wine increased the risk of PCa, whereas moderate consumption of red wine had a protective effect. Further analyses are needed to assess the differential molecular effect of white and red wine conferring their impact on PCa risk.

Q-mode versus R-mode principal component analysis for linear discriminant analysis (LDA)

NASA Astrophysics Data System (ADS)

Lee, Loong Chuen; Liong, Choong-Yeun; Jemain, Abdul Aziz

2017-05-01

Many literature apply Principal Component Analysis (PCA) as either preliminary visualization or variable con-struction methods or both. Focus of PCA can be on the samples (R-mode PCA) or variables (Q-mode PCA). Traditionally, R-mode PCA has been the usual approach to reduce high-dimensionality data before the application of Linear Discriminant Analysis (LDA), to solve classification problems. Output from PCA composed of two new matrices known as loadings and scores matrices. Each matrix can then be used to produce a plot, i.e. loadings plot aids identification of important variables whereas scores plot presents spatial distribution of samples on new axes that are also known as Principal Components (PCs). Fundamentally, the scores matrix always be the input variables for building classification model. A recent paper uses Q-mode PCA but the focus of analysis was not on the variables but instead on the samples. As a result, the authors have exchanged the use of both loadings and scores plots in which clustering of samples was studied using loadings plot whereas scores plot has been used to identify important manifest variables. Therefore, the aim of this study is to statistically validate the proposed practice. Evaluation is based on performance of external error obtained from LDA models according to number of PCs. On top of that, bootstrapping was also conducted to evaluate the external error of each of the LDA models. Results show that LDA models produced by PCs from R-mode PCA give logical performance and the matched external error are also unbiased whereas the ones produced with Q-mode PCA show the opposites. With that, we concluded that PCs produced from Q-mode is not statistically stable and thus should not be applied to problems of classifying samples, but variables. We hope this paper will provide some insights on the disputable issues.

Prospective Quality of Life Outcomes for Low-Risk Prostate Cancer: Active Surveillance versus Radical Prostatectomy

PubMed Central

Jeldres, Claudio; Cullen, Jennifer; Hurwitz, Lauren M.; Wolff, Erika M.; Levie, Katherine; Odem-Davis, Katherine; Johnston, Richard B.; Pham, Khanh N.; Rosner, Inger L; Brand, Timothy C.; L’Esperance, James O.; Sterbis, Joseph R.; Etzioni, Ruth B.; Porter, Christopher R.

2015-01-01

Background For low-risk prostate cancer (PCa), active surveillance (AS) may confer comparable oncological outcomes to radical prostatectomy (RP). Health-related quality of life (HRQoL) outcomes are important to consider, yet few studies have examined HRQoL for patients managed with AS. This study compared longitudinal HRQoL in a prospective, racially diverse, and contemporary cohort of patients who underwent RP or AS for low-risk PCa. Methods Beginning in 2007, HRQoL data from validated questionnaires (EPIC and SF-36) were collected by the Center for Prostate Disease Research in a multi-center national database. Patients aged ≤75 that were diagnosed with low-risk PCa and elected RP or AS for initial disease management were followed for three years. Mean scores were estimated using generalized estimating equations, adjusting for baseline HRQoL, demographic and clinical patient characteristics. Results Of the patients with low-risk PCa, 228 underwent RP and 77 underwent AS. Multivariable analysis revealed that RP patients had significantly worse sexual function, sexual bother, and urinary function at all time points compared to patients on AS. Differences in mental health between groups were below the threshold for clinical significance at one year. Conclusions This study found no differences in mental health outcomes but worse urinary and sexual HRQoL for RP patients compared to AS patients for up to three years. These data offer support for management of low risk PCa with AS as a means for postponing the morbidity associated with RP without concomitant mental health declines. PMID:25845467

Prostate cancer molecular detection in plasma samples by glutathione S-transferase P1 (GSTP1) methylation analysis.

PubMed

Dumache, Raluca; Puiu, Maria; Motoc, Marilena; Vernic, Corina; Dumitrascu, Victor

2014-01-01

Prostate cancer (PCa) represents the most commonly diagnosed type of malignancy among men in Western European countries and the second cause of cancer-related deaths among men worldwide. Methylation of the CpG island has an important role in prostate carcinogenesis and progression. The purpose of the study was to analyse the diagnostic value of aberrant promoter hypermethylation of the gene for glutathione S-transferase P1 (GSTP1) in plasma DNA to discriminate between prostate cancer (PCa) and benign prostatic hyperplasia (BPH) patients by minimally invasive methods. Aberrant promoter hypermethylation was investigated in DNA isolated from plasma samples of 31 patients with diagnostic of PCa and 44 cancer-free males (control subjects). Extracted genomic DNA was bisulfite treated and analyzed using methylation-specific polymerase chain reaction (MS-PCR) technique. Hypermethylation of the GSTP1 gene was detected in plasma samples from 27 of 31 (92.86%) patients with PCa. Genomic DNA from plasma samples from the 44 controls without genitourinary cancer revealed promoter hypermethylation of GSTP1 gene in 3 (10.6%) of the 44 patients. Receiver operating curve (ROC) included clinico-pathological parameters such as: serum PSA levels, pathological stage, Gleason score, hypermethylation status of GSTP1 gene, and it gave a predictive accuracy of 93% with a sensitivity and specificity of 95% and 87%, respectively. In this study, we have evaluated the ability of GSTP1 gene to discriminate between PCa and BPH patients in genomic DNA from plasma samples by non-invasive methods.

Minireview: The Molecular and Genomic Basis for Prostate Cancer Health Disparities

PubMed Central

Bollig-Fischer, Aliccia

2013-01-01

Despite more aggressive screening across all demographics and gradual declines in mortality related to prostate cancer (PCa) in the United States, race disparities persist. For African American men (AAM), PCa is more often an aggressive disease showing increased metastases and greater PCa-related mortality compared with European American men. The earliest research points to how distinctions are likely the result of a combination of factors, including ancestry genetics and lifestyle variables. More recent research considers that cancer, although influenced by external forces, is ultimately a disease primarily driven by aberrations observed in the molecular genetics of the tumor. Research studying PCa predominantly from European American men shows that indolent and advanced or metastatic prostate tumors have distinguishing molecular genomic make-ups. Early yet increasing evidence suggests that clinically distinct PCa from AAM also display molecular distinctions. It is reasonable to predict that further study will reveal molecular subtypes and various frequencies for PCa subtypes among diverse patient groups, thereby providing insight as to the genomic lesions and gene signatures that are functionally implicated in carcinogenesis or aggressive PCa in AAM. That knowledge will prove useful in developing strategies to predict who will develop advanced PCa among AAM and will provide the rationale to develop effective individualized treatment strategies to overcome disparities. PMID:23608645

Tumour-derived alkaline phosphatase regulates tumour growth, epithelial plasticity and disease-free survival in metastatic prostate cancer

PubMed Central

Rao, S R; Snaith, A E; Marino, D; Cheng, X; Lwin, S T; Orriss, I R; Hamdy, F C; Edwards, C M

2017-01-01

Background: Recent evidence suggests that bone-related parameters are the main prognostic factors for overall survival in advanced prostate cancer (PCa), with elevated circulating levels of alkaline phosphatase (ALP) thought to reflect the dysregulated bone formation accompanying distant metastases. We have identified that PCa cells express ALPL, the gene that encodes for tissue nonspecific ALP, and hypothesised that tumour-derived ALPL may contribute to disease progression. Methods: Functional effects of ALPL inhibition were investigated in metastatic PCa cell lines. ALPL gene expression was analysed from published PCa data sets, and correlated with disease-free survival and metastasis. Results: ALPL expression was increased in PCa cells from metastatic sites. A reduction in tumour-derived ALPL expression or ALP activity increased cell death, mesenchymal-to-epithelial transition and reduced migration. Alkaline phosphatase activity was decreased by the EMT repressor Snail. In men with PCa, tumour-derived ALPL correlated with EMT markers, and high ALPL expression was associated with a significant reduction in disease-free survival. Conclusions: Our studies reveal the function of tumour-derived ALPL in regulating cell death and epithelial plasticity, and demonstrate a strong association between ALPL expression in PCa cells and metastasis or disease-free survival, thus identifying tumour-derived ALPL as a major contributor to the pathogenesis of PCa progression. PMID:28006818

Physiological and structural properties of saponin-skinned single smooth muscle cells

PubMed Central

1987-01-01

The study of the fundamental events underlying the generation and regulation of force in smooth muscle would be greatly facilitated if the permeability of the cell membrane were increased so that the intracellular environment of the contractile apparatus could be manipulated experimentally. To initiate such an analysis, we developed a saponin permeabilization procedure that was used to "skin" isolated smooth muscle cells from the stomach of the toad, Bufo marinus. Suspensions of single cells isolated enzymatically were resuspended in high-K+ rigor solution (0 ATP, 5 mM EGTA) and exposed for 5 min to 25 micrograms/ml saponin. Virtually all the cells in a suspension were made permeable by this procedure and shortened to less than one-third their initial length when ATP and Ca++ were added; they re-extended when free Ca++ was removed. Analysis of the protein content of the skinned cells revealed that, although their total protein was reduced by approximately 30%, they retained most of their myosin and actin. Skinning was accompanied by a rearrangement of actin and myosin filaments within the cells such that a fine fibrillar structure became visible under the light microscope and a tight clustering of acting filaments around myosin filaments was revealed by the electron microscope. Face-on views of saponin-treated cell membranes revealed the presence of 70-80-A-wide pits or holes. The shortening rate of skinned cells was sensitive to [Ca++] between pCa 7 and pCa 5 and was half-maximal at approximately pCa 6.2. Shortening was also dependent on [ATP] but could be increased at low [ATP] by pretreatment with adenosine-5'-O-(3-thiotriphosphate) (ATP gamma S), which suggests that myosin phosphorylation was more sensitive to low substrate concentrations than was cross-bridge cycling. To determine whether a significant limitation to free diffusion existed in the skinned cells, a computer model of the cell and the unstirred layer surrounding it was developed. Simulations revealed that the membrane, even in skinned cells, could, for short time intervals, significantly inhibit the movement of substances into and out of cells. PMID:3114416

Physiological and structural properties of saponin-skinned single smooth muscle cells.

PubMed

Kargacin, G J; Fay, F S

1987-07-01

The study of the fundamental events underlying the generation and regulation of force in smooth muscle would be greatly facilitated if the permeability of the cell membrane were increased so that the intracellular environment of the contractile apparatus could be manipulated experimentally. To initiate such an analysis, we developed a saponin permeabilization procedure that was used to "skin" isolated smooth muscle cells from the stomach of the toad, Bufo marinus. Suspensions of single cells isolated enzymatically were resuspended in high-K+ rigor solution (0 ATP, 5 mM EGTA) and exposed for 5 min to 25 micrograms/ml saponin. Virtually all the cells in a suspension were made permeable by this procedure and shortened to less than one-third their initial length when ATP and Ca++ were added; they re-extended when free Ca++ was removed. Analysis of the protein content of the skinned cells revealed that, although their total protein was reduced by approximately 30%, they retained most of their myosin and actin. Skinning was accompanied by a rearrangement of actin and myosin filaments within the cells such that a fine fibrillar structure became visible under the light microscope and a tight clustering of acting filaments around myosin filaments was revealed by the electron microscope. Face-on views of saponin-treated cell membranes revealed the presence of 70-80-A-wide pits or holes. The shortening rate of skinned cells was sensitive to [Ca++] between pCa 7 and pCa 5 and was half-maximal at approximately pCa 6.2. Shortening was also dependent on [ATP] but could be increased at low [ATP] by pretreatment with adenosine-5'-O-(3-thiotriphosphate) (ATP gamma S), which suggests that myosin phosphorylation was more sensitive to low substrate concentrations than was cross-bridge cycling. To determine whether a significant limitation to free diffusion existed in the skinned cells, a computer model of the cell and the unstirred layer surrounding it was developed. Simulations revealed that the membrane, even in skinned cells, could, for short time intervals, significantly inhibit the movement of substances into and out of cells.

A perspective on two chemometrics tools: PCA and MCR, and introduction of a new one: Pattern recognition entropy (PRE), as applied to XPS and ToF-SIMS depth profiles of organic and inorganic materials

NASA Astrophysics Data System (ADS)

Chatterjee, Shiladitya; Singh, Bhupinder; Diwan, Anubhav; Lee, Zheng Rong; Engelhard, Mark H.; Terry, Jeff; Tolley, H. Dennis; Gallagher, Neal B.; Linford, Matthew R.

2018-03-01

X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) are much used analytical techniques that provide information about the outermost atomic and molecular layers of materials. In this work, we discuss the application of multivariate spectral techniques, including principal component analysis (PCA) and multivariate curve resolution (MCR), to the analysis of XPS and ToF-SIMS depth profiles. Multivariate analyses often provide insight into data sets that is not easily obtained in a univariate fashion. Pattern recognition entropy (PRE), which has its roots in Shannon's information theory, is also introduced. This approach is not the same as the mutual information/entropy approaches sometimes used in data processing. A discussion of the theory of each technique is presented. PCA, MCR, and PRE are applied to four different data sets obtained from: a ToF-SIMS depth profile through ca. 100 nm of plasma polymerized C3F6 on Si, a ToF-SIMS depth profile through ca. 100 nm of plasma polymerized PNIPAM (poly (N-isopropylacrylamide)) on Si, an XPS depth profile through a film of SiO2 on Si, and an XPS depth profile through a film of Ta2O5 on Ta. PCA, MCR, and PRE reveal the presence of interfaces in the films, and often indicate that the first few scans in the depth profiles are different from those that follow. PRE and backward difference PRE provide this information in a straightforward fashion. Rises in the PRE signals at interfaces suggest greater complexity to the corresponding spectra. Results from PCA, especially for the higher principal components, were sometimes difficult to understand. MCR analyses were generally more interpretable.

Temporal Processing of Dynamic Positron Emission Tomography via Principal Component Analysis in the Sinogram Domain

NASA Astrophysics Data System (ADS)

Chen, Zhe; Parker, B. J.; Feng, D. D.; Fulton, R.

2004-10-01

In this paper, we compare various temporal analysis schemes applied to dynamic PET for improved quantification, image quality and temporal compression purposes. We compare an optimal sampling schedule (OSS) design, principal component analysis (PCA) applied in the image domain, and principal component analysis applied in the sinogram domain; for region-of-interest quantification, sinogram-domain PCA is combined with the Huesman algorithm to quantify from the sinograms directly without requiring reconstruction of all PCA channels. Using a simulated phantom FDG brain study and three clinical studies, we evaluate the fidelity of the compressed data for estimation of local cerebral metabolic rate of glucose by a four-compartment model. Our results show that using a noise-normalized PCA in the sinogram domain gives similar compression ratio and quantitative accuracy to OSS, but with substantially better precision. These results indicate that sinogram-domain PCA for dynamic PET can be a useful preprocessing stage for PET compression and quantification applications.

An unusual haplotype structure on human chromosome 8p23 derived from the inversion polymorphism.

PubMed

Deng, Libin; Zhang, Yuezheng; Kang, Jian; Liu, Tao; Zhao, Hongbin; Gao, Yang; Li, Chaohua; Pan, Hao; Tang, Xiaoli; Wang, Dunmei; Niu, Tianhua; Yang, Huanming; Zeng, Changqing

2008-10-01

Chromosomal inversion is an important type of genomic variations involved in both evolution and disease pathogenesis. Here, we describe the refined genetic structure of a 3.8-Mb inversion polymorphism at chromosome 8p23. Using HapMap data of 1,073 SNPs generated from 209 unrelated samples from CEPH-Utah residents with ancestry from northern and western Europe (CEU); Yoruba in Ibadan, Nigeria (YRI); and Asian (ASN) samples, which were comprised of Han Chinese from Beijing, China (CHB) and Japanese from Tokyo, Japan (JPT)-we successfully deduced the inversion orientations of all their 418 haplotypes. In particular, distinct haplotype subgroups were identified based on principal component analysis (PCA). Such genetic substructures were consistent with clustering patterns based on neighbor-joining tree reconstruction, which revealed a total of four haplotype clades across all samples. Metaphase fluorescence in situ hybridization (FISH) in a subset of 10 HapMap samples verified their inversion orientations predicted by PCA or phylogenetic tree reconstruction. Positioning of the outgroup haplotype within one of YRI clades suggested that Human NCBI Build 36-inverted order is most likely the ancestral orientation. Furthermore, the population differentiation test and the relative extended haplotype homozygosity (REHH) analysis in this region discovered multiple selection signals, also in a population-specific manner. A positive selection signal was detected at XKR6 in the ASN population. These results revealed the correlation of inversion polymorphisms to population-specific genetic structures, and various selection patterns as possible mechanisms for the maintenance of a large chromosomal rearrangement at 8p23 region during evolution. In addition, our study also showed that haplotype-based clustering methods, such as PCA, can be applied in scanning for cryptic inversion polymorphisms at a genome-wide scale.

Extraction of heavy metals characteristics of the 2011 Tohoku tsunami deposits using multiple classification analysis.

PubMed

Nakamura, Kengo; Kuwatani, Tatsu; Kawabe, Yoshishige; Komai, Takeshi

2016-02-01

Tsunami deposits accumulated on the Tohoku coastal area in Japan due to the impact of the Tohoku-oki earthquake. In the study reported in this paper, we applied principal component analysis (PCA) and cluster analysis (CA) to determine the concentrations of heavy metals in tsunami deposits that had been diluted with water or digested using 1 M HCl. The results suggest that the environmental risk is relatively low, evidenced by the following geometric mean concentrations: Pb, 16 mg kg(-1) and 0.003 ml L(-1); As, 1.8 mg kg(-1) and 0.004 ml L(-1); and Cd, 0.17 mg kg(-1) and 0.0001 ml L(-1). CA was performed after outliers were excluded using PCA. The analysis grouped the concentrations of heavy metals for leaching in water and acid. For the acid case, the first cluster contained Ni, Fe, Cd, Cu, Al, Cr, Zn, and Mn; while the second contained Pb, Sb, As, and Mo. For water, the first cluster contained Ni, Fe, Al, and Cr; and the second cluster contained Mo, Sb, As, Cu, Zn, Pb, and Mn. Statistical analysis revealed that the typical toxic elements, As, Pb, and Cd have steady correlations for acid leaching but are relatively sparse for water leaching. Pb and As from the tsunami deposits seemed to reveal a kind of redox elution mechanism using 1 M HCl. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Lack of association between NAT2 polymorphism and prostate cancer risk: a meta-analysis and trial sequential analysis

PubMed Central

Tang, Jingyuan; Xu, Lingyan; Xu, Haoxiang; Li, Ran; Han, Peng; Yang, Haiwei

2017-01-01

Previous studies have investigated the association between NAT2 polymorphism and the risk of prostate cancer (PCa). However, the findings from these studies remained inconsistent. Hence, we performed a meta-analysis to provide a more reliable conclusion about such associations. In the present meta-analysis, 13 independent case-control studies were included with a total of 14,469 PCa patients and 10,689 controls. All relevant studies published were searched in the databates PubMed, EMBASE, and Web of Science, till March 1st, 2017. We used the pooled odds ratios (ORs) with 95% confidence intervals (CIs) to evaluate the strength of the association between NAT2*4 allele and susceptibility to PCa. Subgroup analysis was carried out by ethnicity, source of controls and genotyping method. What's more, we also performed trial sequential analysis (TSA) to reduce the risk of type I error and evaluate whether the evidence of the results was firm. Firstly, our results indicated that NAT2*4 allele was not associated with PCa susceptibility (OR = 1.00, 95% CI= 0.95–1.05; P = 0.100). However, after excluding two studies for its heterogeneity and publication bias, no significant relationship was also detected between NAT2*4 allele and the increased risk of PCa, in fixed-effect model (OR = 0.99, 95% CI= 0.94–1.04; P = 0.451). Meanwhile, no significant increased risk of PCa was found in the subgroup analyses by ethnicity, source of controls and genotyping method. Moreover, TSA demonstrated that such association was confirmed in the present study. Therefore, this meta-analysis suggested that no significant association between NAT2 polymorphism and the risk of PCa was found. PMID:28915684

Clinical Significance of Retinoic Acid Receptor Beta Promoter Methylation in Prostate Cancer: A Meta-Analysis.

PubMed

Dou, MengMeng; Zhou, XueLiang; Fan, ZhiRui; Ding, XianFei; Li, LiFeng; Wang, ShuLing; Xue, Wenhua; Wang, Hui; Suo, Zhenhe; Deng, XiaoMing

2018-01-01

Retinoic acid receptor beta (RAR beta) is a retinoic acid receptor gene that has been shown to play key roles during multiple cancer processes, including cell proliferation, apoptosis, migration and invasion. Numerous studies have found that methylation of the RAR beta promoter contributed to the occurrence and development of malignant tumors. However, the connection between RAR beta promoter methylation and prostate cancer (PCa) remains unknown. This meta-analysis evaluated the clinical significance of RAR beta promoter methylation in PCa. We searched all published records relevant to RAR beta and PCa in a series of databases, including PubMed, Embase, Cochrane Library, ISI Web of Science and CNKI. The rates of RAR beta promoter methylation in the PCa and control groups (including benign prostatic hyperplasia and normal prostate tissues) were summarized. In addition, we evaluated the source region of available samples and the methods used to detect methylation. To compare the incidence and variation in RAR beta promoter methylation in PCa and non-PCa tissues, the odds ratio (OR) and 95% confidence interval (CI) were calculated accordingly. All the data were analyzed with the statistical software STATA 12.0. Based on the inclusion and exclusion criteria, 15 articles assessing 1,339 samples were further analyzed. These data showed that the RAR beta promoter methylation rates in PCa tissues were significantly higher than the rates in the non-PCa group (OR=21.65, 95% CI: 9.27-50.57). Subgroup analysis according to the source region of samples showed that heterogeneity in Asia was small (I2=0.0%, P=0.430). Additional subgroup analysis based on the method used to detect RAR beta promoter methylation showed that the heterogeneity detected by MSP (methylation-specific PCR) was relatively small (I2=11.3%, P=0.343). Although studies reported different rates for RAR beta promoter methylation in PCa tissues, the total analysis demonstrated that RAR beta promoter methylation may be correlated with PCa carcinogenesis and that the RAR beta gene is particularly susceptible. Additional studies with sufficient data are essential to further evaluate the clinical features and prognostic utility of RAR beta promoter methylation in PCa. © 2018 The Author(s). Published by S. Karger AG, Basel.

Genistein versus ICI 182, 780: an ally or enemy in metastatic progression of prostate cancer.

PubMed

Nakamura, Hisae; Wang, Yuwei; Xue, Hui; Romanish, Mark T; Mager, Dixie L; Helgason, Cheryl D; Wang, Yuzhuo

2013-12-01

Androgen signalling through the androgen receptor (AR) plays a critical role in prostate cancer (PCa) initiation and progression. Estrogen in synergy with androgen is essential for cell growth of the normal and malignant prostate. However, the exact role that estrogen and the estrogen receptor play in prostate carcinogenesis remains unclear. We have previously demonstrated the metastasis-promoting effect of an estrogen receptor beta (ERβ) agonist (genistein) in a patient-derived PCa xenograft model mimicking localized and metastatic disease. To test the hypothesis that the tumor-promoting activity of genistein was due to its estrogenic properties, we treated the xenograft-bearing mice with genistein and an anti-estrogen compound (ICI 182, 780) and compared the differential gene expression using microarrays. Using a second xenograft model which was derived from another patient, we showed that genistein promoted disease progression in vivo and ICI 182, 780 inhibited metastatic spread. The microarray analysis revealed that the metallothionein (MT) gene family was differentially expressed in tumors treated by these compounds. Using qRT-PCR, the differences in expression levels were validated in the metastatic and non-metastatic LTL313 PCa xenograft tumor lines, both of which were originally derived from the same PCa patient. Together our data provide evidence that genistein stimulates and ICI 182, 780 inhibits metastatic progression, suggesting that these effects may be mediated by ERβ signalling. © 2013 Wiley Periodicals, Inc.

Two worlds collide: Image analysis methods for quantifying structural variation in cluster molecular dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steenbergen, K. G., E-mail: kgsteen@gmail.com; Gaston, N.

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement formore » a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.« less

Two worlds collide: image analysis methods for quantifying structural variation in cluster molecular dynamics.

PubMed

Steenbergen, K G; Gaston, N

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement for a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.

PCA-LBG-based algorithms for VQ codebook generation

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Yang, Po-Yuan

2015-04-01

Vector quantisation (VQ) codebooks are generated by combining principal component analysis (PCA) algorithms with Linde-Buzo-Gray (LBG) algorithms. All training vectors are grouped according to the projected values of the principal components. The PCA-LBG-based algorithms include (1) PCA-LBG-Median, which selects the median vector of each group, (2) PCA-LBG-Centroid, which adopts the centroid vector of each group, and (3) PCA-LBG-Random, which randomly selects a vector of each group. The LBG algorithm finds a codebook based on the better vectors sent to an initial codebook by the PCA. The PCA performs an orthogonal transformation to convert a set of potentially correlated variables into a set of variables that are not linearly correlated. Because the orthogonal transformation efficiently distinguishes test image vectors, the proposed PCA-LBG-based algorithm is expected to outperform conventional algorithms in designing VQ codebooks. The experimental results confirm that the proposed PCA-LBG-based algorithms indeed obtain better results compared to existing methods reported in the literature.

Discrimination of Geographical Origin of Asian Garlic Using Isotopic and Chemical Datasets under Stepwise Principal Component Analysis.

PubMed

Liu, Tsang-Sen; Lin, Jhen-Nan; Peng, Tsung-Ren

2018-01-16

Isotopic compositions of δ 2 H, δ 18 O, δ 13 C, and δ 15 N and concentrations of 22 trace elements from garlic samples were analyzed and processed with stepwise principal component analysis (PCA) to discriminate garlic's country of origin among Asian regions including South Korea, Vietnam, Taiwan, and China. Results indicate that there is no single trace-element concentration or isotopic composition that can accomplish the study's purpose and the stepwise PCA approach proposed does allow for discrimination between countries on a regional basis. Sequentially, Step-1 PCA distinguishes garlic's country of origin among Taiwanese, South Korean, and Vietnamese samples; Step-2 PCA discriminates Chinese garlic from South Korean garlic; and Step-3 and Step-4 PCA, Chinese garlic from Vietnamese garlic. In model tests, countries of origin of all audit samples were correctly discriminated by stepwise PCA. Consequently, this study demonstrates that stepwise PCA as applied is a simple and effective approach to discriminating country of origin among Asian garlics. © 2018 American Academy of Forensic Sciences.

Plaque echodensity and textural features are associated with histologic carotid plaque instability.

PubMed

Doonan, Robert J; Gorgui, Jessica; Veinot, Jean P; Lai, Chi; Kyriacou, Efthyvoulos; Corriveau, Marc M; Steinmetz, Oren K; Daskalopoulou, Stella S

2016-09-01

Carotid plaque echodensity and texture features predict cerebrovascular symptomatology. Our purpose was to determine the association of echodensity and textural features obtained from a digital image analysis (DIA) program with histologic features of plaque instability as well as to identify the specific morphologic characteristics of unstable plaques. Patients scheduled to undergo carotid endarterectomy were recruited and underwent carotid ultrasound imaging. DIA was performed to extract echodensity and textural features using Plaque Texture Analysis software (LifeQ Medical Ltd, Nicosia, Cyprus). Carotid plaque surgical specimens were obtained and analyzed histologically. Principal component analysis (PCA) was performed to reduce imaging variables. Logistic regression models were used to determine if PCA variables and individual imaging variables predicted histologic features of plaque instability. Image analysis data from 160 patients were analyzed. Individual imaging features of plaque echolucency and homogeneity were associated with a more unstable plaque phenotype on histology. These results were independent of age, sex, and degree of carotid stenosis. PCA reduced 39 individual imaging variables to five PCA variables. PCA1 and PCA2 were significantly associated with overall plaque instability on histology (both P = .02), whereas PCA3 did not achieve statistical significance (P = .07). DIA features of carotid plaques are associated with histologic plaque instability as assessed by multiple histologic features. Importantly, unstable plaques on histology appear more echolucent and homogeneous on ultrasound imaging. These results are independent of stenosis, suggesting that image analysis may have a role in refining the selection of patients who undergo carotid endarterectomy. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Principal Component Analysis reveals correlation of cavities evolution and functional motions in proteins.

PubMed

Desdouits, Nathan; Nilges, Michael; Blondel, Arnaud

2015-02-01

Protein conformation has been recognized as the key feature determining biological function, as it determines the position of the essential groups specifically interacting with substrates. Hence, the shape of the cavities or grooves at the protein surface appears to drive those functions. However, only a few studies describe the geometrical evolution of protein cavities during molecular dynamics simulations (MD), usually with a crude representation. To unveil the dynamics of cavity geometry evolution, we developed an approach combining cavity detection and Principal Component Analysis (PCA). This approach was applied to four systems subjected to MD (lysozyme, sperm whale myoglobin, Dengue envelope protein and EF-CaM complex). PCA on cavities allows us to perform efficient analysis and classification of the geometry diversity explored by a cavity. Additionally, it reveals correlations between the evolutions of the cavities and structures, and can even suggest how to modify the protein conformation to induce a given cavity geometry. It also helps to perform fast and consensual clustering of conformations according to cavity geometry. Finally, using this approach, we show that both carbon monoxide (CO) location and transfer among the different xenon sites of myoglobin are correlated with few cavity evolution modes of high amplitude. This correlation illustrates the link between ligand diffusion and the dynamic network of internal cavities. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Classification and source determination of medium petroleum distillates by chemometric and artificial neural networks: a self organizing feature approach.

PubMed

Mat-Desa, Wan N S; Ismail, Dzulkiflee; NicDaeid, Niamh

2011-10-15

Three different medium petroleum distillate (MPD) products (white spirit, paint brush cleaner, and lamp oil) were purchased from commercial stores in Glasgow, Scotland. Samples of 10, 25, 50, 75, 90, and 95% evaporated product were prepared, resulting in 56 samples in total which were analyzed using gas chromatography-mass spectrometry. Data sets from the chromatographic patterns were examined and preprocessed for unsupervised multivariate analyses using principal component analysis (PCA), hierarchical cluster analysis (HCA), and a self organizing feature map (SOFM) artificial neural network. It was revealed that data sets comprised of higher boiling point hydrocarbon compounds provided a good means for the classification of the samples and successfully linked highly weathered samples back to their unevaporated counterpart in every case. The classification abilities of SOFM were further tested and validated for their predictive abilities where one set of weather data in each case was withdrawn from the sample set and used as a test set of the retrained network. This revealed SOFM to be an outstanding mechanism for sample discrimination and linkage over the more conventional PCA and HCA methods often suggested for such data analysis. SOFM also has the advantage of providing additional information through the evaluation of component planes facilitating the investigation of underlying variables that account for the classification. © 2011 American Chemical Society

Aroma profile and sensory characteristics of a sulfur dioxide-free mulberry (Morus nigra) wine subjected to non-thermal accelerating aging techniques.

PubMed

Tchabo, William; Ma, Yongkun; Kwaw, Emmanuel; Zhang, Haining; Xiao, Lulu; Tahir, Haroon Elrasheid

2017-10-01

The present study was undertaken to assess accelerating aging effects of high pressure, ultrasound and manosonication on the aromatic profile and sensorial attributes of aged mulberry wines (AMW). A total of 166 volatile compounds were found amongst the AMW. The outcomes of the investigation were presented by means of geometric mean (GM), cluster analysis (CA), principal component analysis (PCA), partial least squares regressions (PLSR) and principal component regression (PCR). GM highlighted 24 organoleptic attributes responsible for the sensorial profile of the AMW. Moreover, CA revealed that the volatile composition of the non-thermal accelerated aged wines differs from that of the conventional aged wines. Besides, PCA discriminated the AMW on the basis of their main sensorial characteristics. Furthermore, PLSR identified 75 aroma compounds which were mainly responsible for the olfactory notes of the AMW. Finally, the overall quality of the AMW was noted to be better predicted by PLSR than PCR. Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of chemometrics in quality control of Turmeric (Curcuma longa) based on Ultra-violet, Fourier transform-infrared and 1H NMR spectroscopy.

PubMed

Gad, Haidy A; Bouzabata, Amel

2017-12-15

Turmeric (Curcuma longa L.) belongs to the family Zingiberaceae that is widely used as a spice in food preparations in addition to its biological activities. UV, FT-IR, 1 H NMR in addition to HPLC were applied to construct a metabolic fingerprint for Turmeric in an attempt to assess its quality. 30 samples were analyzed, and then principal component analysis (PCA) and hierarchical clustering analysis (HCA) were utilized to assess the differences and similarities between collected samples. PCA score plot based on both HPLC and UV spectroscopy showed the same discriminatory pattern, where the samples were segregated into four main groups depending on their total curcuminoids content. The results revealed that UV could be utilized as a simple and rapid alternative for HPLC. However, FT-IR failed to discriminate between the same species. By applying 1 H NMR, the metabolic variability between samples was more evident in the essential oils/fatty acid region. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis of seven salad rocket (Eruca sativa) accessions: The relationships between sensory attributes and volatile and non-volatile compounds.

PubMed

Bell, Luke; Methven, Lisa; Signore, Angelo; Oruna-Concha, Maria Jose; Wagstaff, Carol

2017-03-01

Sensory and chemical analyses were performed on accessions of rocket (Eruca sativa) to determine phytochemical influences on sensory attributes. A trained panel was used to evaluate leaves, and chemical data were obtained for polyatomic ions, amino acids, sugars and organic acids. These chemical data (and data of glucosinolates, flavonols and headspace volatiles previously reported) were used in Principal Component Analysis (PCA) to determine variables statistically important to sensory traits. Significant differences were observed between samples for polyatomic ion and amino acid concentrations. PCA revealed strong, positive correlations between glucosinolates, isothiocyanates and sulfur compounds with bitterness, mustard, peppery, warming and initial heat mouthfeel traits. The ratio between glucosinolates and sugars inferred reduced perception of bitter aftereffects. We highlight the diversity of E. sativa accessions from a sensory and phytochemical standpoint, and the potential for breeders to create varieties that are nutritionally and sensorially superior to existing ones. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Quantitative descriptive analysis and principal component analysis for sensory characterization of Indian milk product cham-cham.

PubMed

Puri, Ritika; Khamrui, Kaushik; Khetra, Yogesh; Malhotra, Ravinder; Devraja, H C

2016-02-01

Promising development and expansion in the market of cham-cham, a traditional Indian dairy product is expected in the coming future with the organized production of this milk product by some large dairies. The objective of this study was to document the extent of variation in sensory properties of market samples of cham-cham collected from four different locations known for their excellence in cham-cham production and to find out the attributes that govern much of variation in sensory scores of this product using quantitative descriptive analysis (QDA) and principal component analysis (PCA). QDA revealed significant (p < 0.05) difference in sensory attributes of cham-cham among the market samples. PCA identified four significant principal components that accounted for 72.4 % of the variation in the sensory data. Factor scores of each of the four principal components which primarily correspond to sweetness/shape/dryness of interior, surface appearance/surface dryness, rancid and firmness attributes specify the location of each market sample along each of the axes in 3-D graphs. These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring attributes of cham-cham that contribute most to its sensory acceptability.

Locomotor Recovery in Spinal Cord Injury: Insights Beyond Walking Speed and Distance.

PubMed

Awai, Lea; Curt, Armin

2016-08-01

Recovery of locomotor function after incomplete spinal cord injury (iSCI) is clinically assessed through walking speed and distance, while improvements in these measures might not be in line with a normalization of gait quality and are, on their own, insensitive at revealing potential mechanisms underlying recovery. The objective of this study was to relate changes of gait parameters to the recovery of walking speed while distinguishing between parameters that rather reflect speed improvements from factors contributing to overall recovery. Kinematic data of 16 iSCI subjects were repeatedly recorded during in-patient rehabilitation. The responsiveness of gait parameters to walking speed was assessed by linear regression. Principal component analysis (PCA) was applied on the multivariate data across time to identify factors that contribute to recovery after iSCI. Parameters of gait cycle and movement dynamics were both responsive and closely related to the recovery of walking speed, which increased by 96%. Multivariate analysis revealed specific gait parameters (intralimb shape normality and consistency) that, although less related to speed increments, loaded highly on principal component one (PC1) (58.6%) explaining the highest proportion of variance (i.e., recovery of outcome over time). Interestingly, measures of hip, knee, and ankle range of motion showed varying degrees of responsiveness (from very high to very low) while not contributing to gait recovery as revealed by PCA. The conjunct application of two analysis methods distinguishes gait parameters that simply reflect increased walking speed from parameters that actually contribute to gait recovery in iSCI. This distinction may be of value for the evaluation of interventions for locomotor recovery.

Efficacy and safety of parecoxib sodium for acute postoperative pain: A meta-analysis.

PubMed

Wei, Wei; Zhao, Tianyun; Li, Yuantao

2013-08-01

This meta-analysis was performed to evaluate the efficacy and safety of parecoxib sodium for acute postoperative pain. PubMed, Cochrane Central Register of Controlled Trials, EBSCO, Springer, Ovid and Chinese National Knowledge Infrastructure (CNKI) databases were searched from January 1999 to January 2013 to comprehensively collect randomized controlled trials (RCTs) of parecoxib sodium for acute postoperative pain. The methodological quality of the included RCTs were assessed and the data were extracted by two reviewers independently according to the Cochrane Handbook. Efficacies and safety (respiratory depression, pruritus, fever, headache, and nausea and vomiting) were pooled using meta-analysis performed by Review Manager 5.1 software. Relative risk (RR) and 95% confidence interval (CI) were calculated in a fixed-effects model. Seven RCTs involving 1,939 patients met the inclusion criteria. The results of the meta-analysis revealed that the rate of 'effective' treatment as described by the patients' global evaluation of study medication (PGESM) was higher in the patient-controlled analgesia (PCA) combined with parecoxib sodium group 24, 48, and 72 h after the initial intravenous dose of 40 mg parecoxib compared with that in the control group [PCA alone; RR=1.41, 95% CI (1.13-1.75); RR=1.25, 95% CI (1.15-1.35); and RR=1.30, 95% CI (1.21-1.40), respectively]. The rate of 'ineffective' treatment in the PCA combined with parecoxib sodium group was lower compared with that of the control group [RR=0.43, 95% CI (0.26-0.72); RR= 0.44, 95% CI (0.34-0.57); and RR= 0.33, 95% CI (0.23-0.48), respectively]. Combination of PCA with parecoxib sodium reduced the incidence of postoperative fever [RR=0.34, 95% CI (0.22-0.53)], as well as nausea and vomiting [RR=0.69, 95% CI (0.57-0.83)]; however, it did not significantly reduce respiratory depression [RR= 0.84, 95% CI (0.38-1.83)], pruritus [RR= 0.91, 95% CI (0.54-1.52)] or headache [RR=0.77, 95% CI (0.47-1.28)]. The combination of PCA with parecoxib sodium successively injected for <3 days significantly increases the scores of PGESM and reduces the incidence of adverse effects and postoperative complications.

Efficacy and safety of parecoxib sodium for acute postoperative pain: A meta-analysis

PubMed Central

WEI, WEI; ZHAO, TIANYUN; LI, YUANTAO

2013-01-01

This meta-analysis was performed to evaluate the efficacy and safety of parecoxib sodium for acute postoperative pain. PubMed, Cochrane Central Register of Controlled Trials, EBSCO, Springer, Ovid and Chinese National Knowledge Infrastructure (CNKI) databases were searched from January 1999 to January 2013 to comprehensively collect randomized controlled trials (RCTs) of parecoxib sodium for acute postoperative pain. The methodological quality of the included RCTs were assessed and the data were extracted by two reviewers independently according to the Cochrane Handbook. Efficacies and safety (respiratory depression, pruritus, fever, headache, and nausea and vomiting) were pooled using meta-analysis performed by Review Manager 5.1 software. Relative risk (RR) and 95% confidence interval (CI) were calculated in a fixed-effects model. Seven RCTs involving 1,939 patients met the inclusion criteria. The results of the meta-analysis revealed that the rate of ‘effective’ treatment as described by the patients’ global evaluation of study medication (PGESM) was higher in the patient-controlled analgesia (PCA) combined with parecoxib sodium group 24, 48, and 72 h after the initial intravenous dose of 40 mg parecoxib compared with that in the control group [PCA alone; RR=1.41, 95% CI (1.13–1.75); RR=1.25, 95% CI (1.15–1.35); and RR=1.30, 95% CI (1.21–1.40), respectively]. The rate of ‘ineffective’ treatment in the PCA combined with parecoxib sodium group was lower compared with that of the control group [RR=0.43, 95% CI (0.26–0.72); RR= 0.44, 95% CI (0.34–0.57); and RR= 0.33, 95% CI (0.23–0.48), respectively]. Combination of PCA with parecoxib sodium reduced the incidence of postoperative fever [RR=0.34, 95% CI (0.22–0.53)], as well as nausea and vomiting [RR=0.69, 95% CI (0.57–0.83)]; however, it did not significantly reduce respiratory depression [RR= 0.84, 95% CI (0.38–1.83)], pruritus [RR= 0.91, 95% CI (0.54–1.52)] or headache [RR=0.77, 95% CI (0.47–1.28)]. The combination of PCA with parecoxib sodium successively injected for <3 days significantly increases the scores of PGESM and reduces the incidence of adverse effects and postoperative complications. PMID:24137220

A probability index for surface zonda wind occurrence at Mendoza city through vertical sounding principal components analysis

NASA Astrophysics Data System (ADS)

Otero, Federico; Norte, Federico; Araneo, Diego

2018-01-01

The aim of this work is to obtain an index for predicting the probability of occurrence of zonda event at surface level from sounding data at Mendoza city, Argentine. To accomplish this goal, surface zonda wind events were previously found with an objective classification method (OCM) only considering the surface station values. Once obtained the dates and the onset time of each event, the prior closest sounding for each event was taken to realize a principal component analysis (PCA) that is used to identify the leading patterns of the vertical structure of the atmosphere previously to a zonda wind event. These components were used to construct the index model. For the PCA an entry matrix of temperature ( T) and dew point temperature (Td) anomalies for the standard levels between 850 and 300 hPa was build. The analysis yielded six significant components with a 94 % of the variance explained and the leading patterns of favorable weather conditions for the development of the phenomenon were obtained. A zonda/non-zonda indicator c can be estimated by a logistic multiple regressions depending on the PCA component loadings, determining a zonda probability index \\widehat{c} calculable from T and Td profiles and it depends on the climatological features of the region. The index showed 74.7 % efficiency. The same analysis was performed by adding surface values of T and Td from Mendoza Aero station increasing the index efficiency to 87.8 %. The results revealed four significantly correlated PCs with a major improvement in differentiating zonda cases and a reducing of the uncertainty interval.

Exploring objective climate classification for the Himalayan arc and adjacent regions using gridded data sources

NASA Astrophysics Data System (ADS)

Forsythe, N.; Blenkinsop, S.; Fowler, H. J.

2015-05-01

A three-step climate classification was applied to a spatial domain covering the Himalayan arc and adjacent plains regions using input data from four global meteorological reanalyses. Input variables were selected based on an understanding of the climatic drivers of regional water resource variability and crop yields. Principal component analysis (PCA) of those variables and k-means clustering on the PCA outputs revealed a reanalysis ensemble consensus for eight macro-climate zones. Spatial statistics of input variables for each zone revealed consistent, distinct climatologies. This climate classification approach has potential for enhancing assessment of climatic influences on water resources and food security as well as for characterising the skill and bias of gridded data sets, both meteorological reanalyses and climate models, for reproducing subregional climatologies. Through their spatial descriptors (area, geographic centroid, elevation mean range), climate classifications also provide metrics, beyond simple changes in individual variables, with which to assess the magnitude of projected climate change. Such sophisticated metrics are of particular interest for regions, including mountainous areas, where natural and anthropogenic systems are expected to be sensitive to incremental climate shifts.

Identification of the isomers using principal component analysis (PCA) method

NASA Astrophysics Data System (ADS)

Kepceoǧlu, Abdullah; Gündoǧdu, Yasemin; Ledingham, Kenneth William David; Kilic, Hamdi Sukur

2016-03-01

In this work, we have carried out a detailed statistical analysis for experimental data of mass spectra from xylene isomers. Principle Component Analysis (PCA) was used to identify the isomers which cannot be distinguished using conventional statistical methods for interpretation of their mass spectra. Experiments have been carried out using a linear TOF-MS coupled to a femtosecond laser system as an energy source for the ionisation processes. We have performed experiments and collected data which has been analysed and interpreted using PCA as a multivariate analysis of these spectra. This demonstrates the strength of the method to get an insight for distinguishing the isomers which cannot be identified using conventional mass analysis obtained through dissociative ionisation processes on these molecules. The PCA results dependending on the laser pulse energy and the background pressure in the spectrometers have been presented in this work.

Delineation of Stenotrophomonas maltophilia isolates from cystic fibrosis patients by fatty acid methyl ester profiles and matrix-assisted laser desorption/ionization time-of-flight mass spectra using hierarchical cluster analysis and principal component analysis.

PubMed

Vidigal, Pedrina Gonçalves; Mosel, Frank; Koehling, Hedda Luise; Mueller, Karl Dieter; Buer, Jan; Rath, Peter Michael; Steinmann, Joerg

2014-12-01

Stenotrophomonas maltophilia is an opportunist multidrug-resistant pathogen that causes a wide range of nosocomial infections. Various cystic fibrosis (CF) centres have reported an increasing prevalence of S. maltophilia colonization/infection among patients with this disease. The purpose of this study was to assess specific fingerprints of S. maltophilia isolates from CF patients (n = 71) by investigating fatty acid methyl esters (FAMEs) through gas chromatography (GC) and highly abundant proteins by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), and to compare them with isolates obtained from intensive care unit (ICU) patients (n = 20) and the environment (n = 11). Principal component analysis (PCA) of GC-FAME patterns did not reveal a clustering corresponding to distinct CF, ICU or environmental types. Based on the peak area index, it was observed that S. maltophilia isolates from CF patients produced significantly higher amounts of fatty acids in comparison with ICU patients and the environmental isolates. Hierarchical cluster analysis (HCA) based on the MALDI-TOF MS peak profiles of S. maltophilia revealed the presence of five large clusters, suggesting a high phenotypic diversity. Although HCA of MALDI-TOF mass spectra did not result in distinct clusters predominantly composed of CF isolates, PCA revealed the presence of a distinct cluster composed of S. maltophilia isolates from CF patients. Our data suggest that S. maltophilia colonizing CF patients tend to modify not only their fatty acid patterns but also their protein patterns as a response to adaptation in the unfavourable environment of the CF lung. © 2014 The Authors.

Combination of 1H nuclear magnetic resonance spectroscopy and principal component analysis to evaluate the lipid fluidity of flutamide-encapsulated lipid nanoemulsions.

PubMed

Takegami, Shigehiko; Ueyama, Keita; Konishi, Atsuko; Kitade, Tatsuya

2018-06-06

The lipid fluidity of various lipid nanoemulsions (LNEs) without and with flutamide (FT) and containing one of two neutral lipids, one of four phosphatidylcholines as a surfactant, and sodium palmitate as a cosurfactant was investigated by the combination of 1 H nuclear magnetic resonance (NMR) spectroscopy and principal component analysis (PCA). In the 1 H NMR spectra, the peaks from the methylene groups of the neutral lipids and surfactants for all LNE preparations showed downfield shifts with increasing temperature from 20 to 60 °C. PCA was applied to the 1 H NMR spectral data obtained for the LNEs. The PCA resulted in a model in which the first two principal components (PCs) extracted 88% of the total spectral variation; the first PC (PC-1) axis and second PC (PC-2) axis accounted for 73 and 15%, respectively, of the total spectral variation. The Score-1 values for PC-1 plotted against temperature revealed the existence of two clusters, which were defined by the neutral lipid of the LNE preparations. Meanwhile, the Score-2 values decreased with rising temperature and reflected the increase in lipid fluidity of each LNE preparation, consistent with fluorescence anisotropy measurements. In addition, the changes of Score-2 values with temperature for LNE preparations with FT were smaller than those for LNE preparations without FT. This indicates that FT encapsulated in LNE particles markedly suppressed the increase in lipid fluidity of LNE particles with rising temperature. Thus, PCA of 1 H NMR spectra will become a powerful tool to analyze the lipid fluidity of lipid nanoparticles. Graphical abstract ᅟ.

Degradation of oil products in a soil from a Russian Barents hot-spot during electrodialytic remediation.

PubMed

Pedersen, Kristine B; Lejon, Tore; Jensen, Pernille E; Ottosen, Lisbeth M

2016-01-01

A highly oil-polluted soil from Krasnoe in North-West Russia was used to investigate the degradation of organic pollutants during electrodialytic remediation. Removal efficiencies were up to 70 % for total hydrocarbons (THC) and up to 65 % for polyaromatic hydrocarbons (PAH). Relatively more of the lighter PAH compounds and THC fractions were degraded. A principal component analysis (PCA) revealed a difference in the distribution of PAH compounds after the remediation. The observed clustering of experiments in the PCA scores plot was assessed to be related to the stirring rate. Multivariate analysis of the experimental settings and final concentrations in the 12 experiments revealed that the stirring rate of the soil suspension was by far the most important parameter for the remediation for both THC and PAH. Light was the second most important variable for PAH and seems to influence degradation. The experimental variables current density and remediation time did not significantly influence the degradation of the organic pollutants. Despite current density not influencing the remediation, there is potential for degrading organic pollutants during electrodialytic removal of heavy metals, as long as a stirred set-up is applied. Depending on remediation objectives, further optimisation may be needed in order to develop efficient remediation strategies.

Prostate cancer gene 3 and multiparametric magnetic resonance can reduce unnecessary biopsies: decision curve analysis to evaluate predictive models.

PubMed

Busetto, Gian Maria; De Berardinis, Ettore; Sciarra, Alessandro; Panebianco, Valeria; Giovannone, Riccardo; Rosato, Stefano; D'Errigo, Paola; Di Silverio, Franco; Gentile, Vincenzo; Salciccia, Stefano

2013-12-01

To overcome the well-known prostate-specific antigen limits, several new biomarkers have been proposed. Since its introduction in clinical practice, the urinary prostate cancer gene 3 (PCA3) assay has shown promising results for prostate cancer (PC) detection. Furthermore, multiparametric magnetic resonance imaging (mMRI) has the ability to better describe several aspects of PC. A prospective study of 171 patients with negative prostate biopsy findings and a persistent high prostate-specific antigen level was conducted to assess the role of mMRI and PCA3 in identifying PC. All patients underwent the PCA3 test and mMRI before a second transrectal ultrasound-guided prostate biopsy. The accuracy and reliability of PCA3 (3 different cutoff points) and mMRI were evaluated. Four multivariate logistic regression models were analyzed, in terms of discrimination and the cost benefit, to assess the clinical role of PCA3 and mMRI in predicting the biopsy outcome. A decision curve analysis was also plotted. Repeated transrectal ultrasound-guided biopsy identified 68 new cases (41.7%) of PC. The sensitivity and specificity of the PCA3 test and mMRI was 68% and 49% and 74% and 90%, respectively. Evaluating the regression models, the best discrimination (area under the curve 0.808) was obtained using the full model (base clinical model plus mMRI and PCA3). The decision curve analysis, to evaluate the cost/benefit ratio, showed good performance in predicting PC with the model that included mMRI and PCA3. mMRI increased the accuracy and sensitivity of the PCA3 test, and the use of the full model significantly improved the cost/benefit ratio, avoiding unnecessary biopsies. Copyright © 2013 Elsevier Inc. All rights reserved.

Leupaxin acts as a mediator in prostate carcinoma progression through deregulation of p120catenin expression.

PubMed

Kaulfuss, S; von Hardenberg, S; Schweyer, S; Herr, A M; Laccone, F; Wolf, S; Burfeind, P

2009-11-12

Recently, we could show that the focal adhesion protein leupaxin (LPXN) is expressed in human prostate carcinomas (PCa) and induces invasiveness of androgen-independent PCa cells. In this study we show that LPXN enhanced the progression of existing PCa in vivo by breeding transgenic mice with prostate-specific LPXN expression and TRAMP mice (transgenic adenocarcinoma of mouse prostate). Double transgenic LPXN/TRAMP mice showed a significant increase in poorly differentiated PCa and distant metastases as compared with control TRAMP mice. Additional studies on primary PCa cells generated from both transgenic backgrounds confirmed the connection regarding LPXN overexpression and increased motility and invasiveness of PCa cells. One mediator of LPXN-induced invasion was found to be the cell-cell adhesion protein p120catenin (p120CTN). Both in vitro and in vivo experiments revealed that p120CTN expression negatively correlates with LPXN expression, followed by a redistribution of beta-catenin. Downregulation of LPXN using small interfering RNAs (siRNAs) resulted in a membranous localization of beta-catenin, whereas strong nuclear accumulation of beta-catenin was observed in p120CTN knockdown cells leading to enhanced transcription of the beta-catenin target gene matrix metalloprotease-7. In conclusion, the present results indicate that LPXN enhances the progression of PCa through downregulation of p120CTN expression and that LPXN could function as a marker for aggressive PCa in the future.

Leupaxin stimulates adhesion and migration of prostate cancer cells through modulation of the phosphorylation status of the actin-binding protein caldesmon

PubMed Central

Schmidt, Thomas; Bremmer, Felix; Burfeind, Peter; Kaulfuß, Silke

2015-01-01

The focal adhesion protein leupaxin (LPXN) is overexpressed in a subset of prostate cancers (PCa) and is involved in the progression of PCa. In the present study, we analyzed the LPXN-mediated adhesive and cytoskeletal changes during PCa progression. We identified an interaction between the actin-binding protein caldesmon (CaD) and LPXN and this interaction is increased during PCa cell migration. Furthermore, knockdown of LPXN did not affect CaD expression but reduced CaD phosphorylation. This is known to destabilize the affinity of CaD to F-actin, leading to dynamic cell structures that enable cell motility. Thus, downregulation of CaD increased migration and invasion of PCa cells. To identify the kinase responsible for the LPXN-mediated phosphorylation of CaD, we used data from an antibody array, which showed decreased expression of TGF-beta-activated kinase 1 (TAK1) after LPXN knockdown in PC-3 PCa cells. Subsequent analyses of the downstream kinases revealed the extracellular signal-regulated kinase (ERK) as an interaction partner of LPXN that facilitates CaD phosphorylation during LPXN-mediated PCa cell migration. In conclusion, we demonstrate that LPXN directly influences cytoskeletal dynamics via interaction with the actin-binding protein CaD and regulates CaD phosphorylation by recruiting ERK to highly dynamic structures within PCa cells. PMID:26079947

A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

PubMed

Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J

2015-01-01

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.

A Stock Market Forecasting Model Combining Two-Directional Two-Dimensional Principal Component Analysis and Radial Basis Function Neural Network

PubMed Central

Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J.

2015-01-01

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron. PMID:25849483

Depressed Frank-Starling mechanism in the left ventricular muscle of the knock-in mouse model of dilated cardiomyopathy with troponin T deletion mutation ΔK210.

PubMed

Inoue, Takahiro; Kobirumaki-Shimozawa, Fuyu; Kagemoto, Tatsuya; Fujii, Teruyuki; Terui, Takako; Kusakari, Yoichiro; Hongo, Kenichi; Morimoto, Sachio; Ohtsuki, Iwao; Hashimoto, Kazuhiro; Fukuda, Norio

2013-10-01

It has been reported that the Frank-Starling mechanism is coordinately regulated in cardiac muscle via thin filament "on-off" equilibrium and titin-based lattice spacing changes. In the present study, we tested the hypothesis that the deletion mutation ΔK210 in the cardiac troponin T gene shifts the equilibrium toward the "off" state and accordingly attenuate the sarcomere length (SL) dependence of active force production, via reduced cross-bridge formation. Confocal imaging in isolated hearts revealed that the cardiomyocytes were enlarged, especially in the longitudinal direction, in ΔK210 hearts, with striation patterns similar to those in wild type (WT) hearts, suggesting that the number of sarcomeres is increased in cardiomyocytes but the sarcomere length remains unaltered. For analysis of the SL dependence of active force, skinned muscle preparations were obtained from the left ventricle of WT and knock-in (ΔK210) mice. An increase in SL from 1.90 to 2.20μm shifted the mid-point (pCa50) of the force-pCa curve leftward by ~0.21pCa units in WT preparations. In ΔK210 muscles, Ca(2+) sensitivity was lower by ~0.37pCa units, and the SL-dependent shift of pCa50, i.e., ΔpCa50, was less pronounced (~0.11pCa units), with and without protein kinase A treatment. The rate of active force redevelopment was lower in ΔK210 preparations than in WT preparations, showing blunted thin filament cooperative activation. An increase in thin filament cooperative activation upon an increase in the fraction of strongly bound cross-bridges by MgADP increased ΔpCa50 to ~0.21pCa units. The depressed Frank-Starling mechanism in ΔK210 hearts is the result of a reduction in thin filament cooperative activation. © 2013.

Application of EOF/PCA-based methods in the post-processing of GRACE derived water variations

NASA Astrophysics Data System (ADS)

Forootan, Ehsan; Kusche, Jürgen

2010-05-01

Two problems that users of monthly GRACE gravity field solutions face are 1) the presence of correlated noise in the Stokes coefficients that increases with harmonic degree and causes ‘striping', and 2) the fact that different physical signals are overlaid and difficult to separate from each other in the data. These problems are termed the signal-noise separation problem and the signal-signal separation problem. Methods that are based on principal component analysis and empirical orthogonal functions (PCA/EOF) have been frequently proposed to deal with these problems for GRACE. However, different strategies have been applied to different (spatial: global/regional, spectral: global/order-wise, geoid/equivalent water height) representations of the GRACE level 2 data products, leading to differing results and a general feeling that PCA/EOF-based methods are to be applied ‘with care'. In addition, it is known that conventional EOF/PCA methods force separated modes to be orthogonal, and that, on the other hand, to either EOFs or PCs an arbitrary orthogonal rotation can be applied. The aim of this paper is to provide a common theoretical framework and to study the application of PCA/EOF-based methods as a signal separation tool due to post-process GRACE data products. In order to investigate and illustrate the applicability of PCA/EOF-based methods, we have employed them on GRACE level 2 monthly solutions based on the Center for Space Research, University of Texas (CSR/UT) RL04 products and on the ITG-GRACE03 solutions from the University of Bonn, and on various representations of them. Our results show that EOF modes do reveal the dominating annual, semiannual and also long-periodic signals in the global water storage variations, but they also show how choosing different strategies changes the outcome and may lead to unexpected results.

ANALYSIS OF TMEFF2 ALLOGRAFTS AND TRANSGENIC MOUSE MODELS REVEALS ROLES IN PROSTATE REGENERATION AND CANCER

PubMed Central

Corbin, JM.; Overcash, RF.; Wren, JD.; Coburn, A.; Tipton, GJ.; Ezzell, JA.; McNaughton, KK.; Fung, KM; Kosanke, SD.; Ruiz-Echevarria, MJ

2015-01-01

BACKGROUND Previous results from our lab indicate a tumor suppressor role for the transmembrane protein with epidermal growth factor and two follistatin motifs 2 (TMEFF2) in prostate cancer (PCa). Here, we further characterize this role and uncover new functions for TMEFF2 in cancer and adult prostate regeneration. METHODS The role of TMEFF2 was examined in PCa cells using Matrigel™ cultures and allograft models of PCa cells. In addition, we developed a transgenic mouse model that expresses TMEFF2 from a prostate specific promoter. Anatomical, histological and metabolic characterizations of the transgenic mouse prostate were conducted. The effect of TMEFF2 in prostate regeneration was studied by analyzing branching morphogenesis in the TMEFF2-expressing mouse lobes and alterations in branching morphogenesis were correlated with the metabolomic profiles of the mouse lobes. The role of TMEFF2 in prostate tumorigenesis in whole animals was investigated by crossing the TMEFF2 transgenic mice with the TRAMP mouse model of PCa and analyzing the histopathological changes in the progeny. RESULTS Ectopic expression of TMEFF2 impairs growth of PCa cells in Matrigel or allograft models. Surprisingly, while TMEFF2 expression in the TRAMP mouse did not have a significant effect on the glandular prostate epithelial lesions, the double TRAMP/TMEFF2 transgenic mice displayed an increased incidence of neuroendocrine type tumors. In addition, TMEFF2 promoted increased branching specifically in the dorsal lobe of the prostate suggesting a potential role in developmental processes. These results correlated with data indicating an alteration in the metabolic profile of the dorsal lobe of the transgenic TMEFF2 mice. CONCLUSIONS Collectively, our results confirm the tumor suppressor role of TMEFF2 and suggest that ectopic expression of TMEFF2 in mouse prostate leads to additional lobe-specific effects in prostate regeneration and tumorigenesis. This points to a complex and multifunctional role for TMEFF2 during PCa progression. PMID:26417683

Analysis of TMEFF2 allografts and transgenic mouse models reveals roles in prostate regeneration and cancer.

PubMed

Corbin, Joshua M; Overcash, Ryan F; Wren, Jonathan D; Coburn, Anita; Tipton, Greg J; Ezzell, Jennifer A; McNaughton, Kirk K; Fung, Kar-Ming; Kosanke, Stanley D; Ruiz-Echevarria, Maria J

2016-01-01

Previous results from our lab indicate a tumor suppressor role for the transmembrane protein with epidermal growth factor and two follistatin motifs 2 (TMEFF2) in prostate cancer (PCa). Here, we further characterize this role and uncover new functions for TMEFF2 in cancer and adult prostate regeneration. The role of TMEFF2 was examined in PCa cells using Matrigel(TM) cultures and allograft models of PCa cells. In addition, we developed a transgenic mouse model that expresses TMEFF2 from a prostate specific promoter. Anatomical, histological, and metabolic characterizations of the transgenic mouse prostate were conducted. The effect of TMEFF2 in prostate regeneration was studied by analyzing branching morphogenesis in the TMEFF2-expressing mouse lobes and alterations in branching morphogenesis were correlated with the metabolomic profiles of the mouse lobes. The role of TMEFF2 in prostate tumorigenesis in whole animals was investigated by crossing the TMEFF2 transgenic mice with the TRAMP mouse model of PCa and analyzing the histopathological changes in the progeny. Ectopic expression of TMEFF2 impairs growth of PCa cells in Matrigel or allograft models. Surprisingly, while TMEFF2 expression in the TRAMP mouse did not have a significant effect on the glandular prostate epithelial lesions, the double TRAMP/TMEFF2 transgenic mice displayed an increased incidence of neuroendocrine type tumors. In addition, TMEFF2 promoted increased branching specifically in the dorsal lobe of the prostate suggesting a potential role in developmental processes. These results correlated with data indicating an alteration in the metabolic profile of the dorsal lobe of the transgenic TMEFF2 mice. Collectively, our results confirm the tumor suppressor role of TMEFF2 and suggest that ectopic expression of TMEFF2 in mouse prostate leads to additional lobe-specific effects in prostate regeneration and tumorigenesis. This points to a complex and multifunctional role for TMEFF2 during PCa progression. © 2015 Wiley Periodicals, Inc.

Delusions in first-episode psychosis: Principal component analysis of twelve types of delusions and demographic and clinical correlates of resulting domains.

PubMed

Paolini, Enrico; Moretti, Patrizia; Compton, Michael T

2016-09-30

Although delusions represent one of the core symptoms of psychotic disorders, it is remarkable that few studies have investigated distinct delusional themes. We analyzed data from a large sample of first-episode psychosis patients (n=245) to understand relations between delusion types and demographic and clinical correlates. First, we conducted a principal component analysis (PCA) of the 12 delusion items within the Scale for the Assessment of Positive Symptoms (SAPS). Then, using the domains derived via PCA, we tested a priori hypotheses and answered exploratory research questions related to delusional content. PCA revealed five distinct components: Delusions of Influence, Grandiose/Religious Delusions, Paranoid Delusions, Negative Affect Delusions (jealousy, and sin or guilt), and Somatic Delusions. The most prevalent type of delusion was Paranoid Delusions, and such delusions were more common at older ages at onset of psychosis. The level of Delusions of Influence was correlated with the severity of hallucinations and negative symptoms. We ascertained a general relationship between different childhood adversities and delusional themes, and a specific relationship between Somatic Delusions and childhood neglect. Moreover, we found higher scores on Delusions of Influence and Negative Affect Delusions among cannabis and stimulant users. Our results support considering delusions as varied experiences with varying prevalences and correlates. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Dynamic Responses in Brain Networks to Social Feedback: A Dual EEG Acquisition Study in Adolescent Couples

PubMed Central

Kuo, Ching-Chang; Ha, Thao; Ebbert, Ashley M.; Tucker, Don M.; Dishion, Thomas J.

2017-01-01

Adolescence is a sensitive period for the development of romantic relationships. During this period the maturation of frontolimbic networks is particularly important for the capacity to regulate emotional experiences. In previous research, both functional magnetic resonance imaging (fMRI) and dense array electroencephalography (dEEG) measures have suggested that responses in limbic regions are enhanced in adolescents experiencing social rejection. In the present research, we examined social acceptance and rejection from romantic partners as they engaged in a Chatroom Interact Task. Dual 128-channel dEEG systems were used to record neural responses to acceptance and rejection from both adolescent romantic partners and unfamiliar peers (N = 75). We employed a two-step temporal principal component analysis (PCA) and spatial independent component analysis (ICA) approach to statistically identify the neural components related to social feedback. Results revealed that the early (288 ms) discrimination between acceptance and rejection reflected by the P3a component was significant for the romantic partner but not the unfamiliar peer. In contrast, the later (364 ms) P3b component discriminated between acceptance and rejection for both partners and peers. The two-step approach (PCA then ICA) was better able than either PCA or ICA alone in separating these components of the brain's electrical activity that reflected both temporal and spatial phases of the brain's processing of social feedback. PMID:28620292

Identification and classification of upper limb motions using PCA.

PubMed

Veer, Karan; Vig, Renu

2018-03-28

This paper describes the utility of principal component analysis (PCA) in classifying upper limb signals. PCA is a powerful tool for analyzing data of high dimension. Here, two different input strategies were explored. The first method uses upper arm dual-position-based myoelectric signal acquisition and the other solely uses PCA for classifying surface electromyogram (SEMG) signals. SEMG data from the biceps and the triceps brachii muscles and four independent muscle activities of the upper arm were measured in seven subjects (total dataset=56). The datasets used for the analysis are rotated by class-specific principal component matrices to decorrelate the measured data prior to feature extraction.

Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer.

PubMed

White-Al Habeeb, Nicole M A; Ho, Linh T; Olkhov-Mitsel, Ekaterina; Kron, Ken; Pethe, Vaijayanti; Lehman, Melanie; Jovanovic, Lidija; Fleshner, Neil; van der Kwast, Theodorus; Nelson, Colleen C; Bapat, Bharati

2014-09-15

Epigenetic silencing mediated by CpG methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with tumor progression may identify potential prognostic markers for prostate cancer (PCa). We treated two PCa cell lines, 22Rv1 and DU-145 with the demethylating agent 5-Aza 2'-deoxycitidine (DAC) and global methylation status was analyzed by performing methylation-sensitive restriction enzyme based differential methylation hybridization strategy followed by genome-wide CpG methylation array profiling. In addition, we examined gene expression changes using a custom microarray. Gene Set Enrichment Analysis (GSEA) identified the most significantly dysregulated pathways. In addition, we assessed methylation status of candidate genes that showed reduced CpG methylation and increased gene expression after DAC treatment, in Gleason score (GS) 8 vs. GS6 patients using three independent cohorts of patients; the publically available The Cancer Genome Atlas (TCGA) dataset, and two separate patient cohorts. Our analysis, by integrating methylation and gene expression in PCa cell lines, combined with patient tumor data, identified novel potential biomarkers for PCa patients. These markers may help elucidate the pathogenesis of PCa and represent potential prognostic markers for PCa patients.

The impact of moderate wine consumption on the risk of developing prostate cancer

PubMed Central

Ferro, Matteo; Foerster, Beat; Abufaraj, Mohammad; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2018-01-01

Objective To investigate the impact of moderate wine consumption on the risk of prostate cancer (PCa). We focused on the differential effect of moderate consumption of red versus white wine. Design This study was a meta-analysis that includes data from case–control and cohort studies. Materials and methods A systematic search of Web of Science, Medline/PubMed, and Cochrane library was performed on December 1, 2017. Studies were deemed eligible if they assessed the risk of PCa due to red, white, or any wine using multivariable logistic regression analysis. We performed a formal meta-analysis for the risk of PCa according to moderate wine and wine type consumption (white or red). Heterogeneity between studies was assessed using Cochrane’s Q test and I2 statistics. Publication bias was assessed using Egger’s regression test. Results A total of 930 abstracts and titles were initially identified. After removal of duplicates, reviews, and conference abstracts, 83 full-text original articles were screened. Seventeen studies (611,169 subjects) were included for final evaluation and fulfilled the inclusion criteria. In the case of moderate wine consumption: the pooled risk ratio (RR) for the risk of PCa was 0.98 (95% CI 0.92–1.05, p=0.57) in the multivariable analysis. Moderate white wine consumption increased the risk of PCa with a pooled RR of 1.26 (95% CI 1.10–1.43, p=0.001) in the multi-variable analysis. Meanwhile, moderate red wine consumption had a protective role reducing the risk by 12% (RR 0.88, 95% CI 0.78–0.999, p=0.047) in the multivariable analysis that comprised 222,447 subjects. Conclusions In this meta-analysis, moderate wine consumption did not impact the risk of PCa. Interestingly, regarding the type of wine, moderate consumption of white wine increased the risk of PCa, whereas moderate consumption of red wine had a protective effect. Further analyses are needed to assess the differential molecular effect of white and red wine conferring their impact on PCa risk. PMID:29713200

Visible micro-Raman spectroscopy of single human mammary epithelial cells exposed to x-ray radiation.

PubMed

Delfino, Ines; Perna, Giuseppe; Lasalvia, Maria; Capozzi, Vito; Manti, Lorenzo; Camerlingo, Carlo; Lepore, Maria

2015-03-01

A micro-Raman spectroscopy investigation has been performed in vitro on single human mammary epithelial cells after irradiation by graded x-ray doses. The analysis by principal component analysis (PCA) and interval-PCA (i-PCA) methods has allowed us to point out the small differences in the Raman spectra induced by irradiation. This experimental approach has enabled us to delineate radiation-induced changes in protein, nucleic acid, lipid, and carbohydrate content. In particular, the dose dependence of PCA and i-PCA components has been analyzed. Our results have confirmed that micro-Raman spectroscopy coupled to properly chosen data analysis methods is a very sensitive technique to detect early molecular changes at the single-cell level following exposure to ionizing radiation. This would help in developing innovative approaches to monitor radiation cancer radiotherapy outcome so as to reduce the overall radiation dose and minimize damage to the surrounding healthy cells, both aspects being of great importance in the field of radiation therapy.

Whole milk intake is associated with prostate cancer-specific mortality among U.S. male physicians.

PubMed

Song, Yan; Chavarro, Jorge E; Cao, Yin; Qiu, Weiliang; Mucci, Lorelei; Sesso, Howard D; Stampfer, Meir J; Giovannucci, Edward; Pollak, Michael; Liu, Simin; Ma, Jing

2013-02-01

Previous studies have associated higher milk intake with greater prostate cancer (PCa) incidence, but little data are available concerning milk types and the relation between milk intake and risk of fatal PCa. We investigated the association between intake of dairy products and the incidence and survival of PCa during a 28-y follow-up. We conducted a cohort study in the Physicians' Health Study (n = 21,660) and a survival analysis among the incident PCa cases (n = 2806). Information on dairy product consumption was collected at baseline. PCa cases and deaths (n = 305) were confirmed during follow-up. The intake of total dairy products was associated with increased PCa incidence [HR = 1.12 (95% CI: 0.93, 1.35); >2.5 servings/d vs. ≤0.5 servings/d]. Skim/low-fat milk intake was positively associated with risk of low-grade, early stage, and screen-detected cancers, whereas whole milk intake was associated only with fatal PCa [HR = 1.49 (95% CI: 0.97, 2.28); ≥237 mL/d (1 serving/d) vs. rarely consumed]. In the survival analysis, whole milk intake remained associated with risk of progression to fatal disease after diagnosis [HR = 2.17 (95% CI: 1.34, 3.51)]. In this prospective cohort, higher intake of skim/low-fat milk was associated with a greater risk of nonaggressive PCa. Most importantly, only whole milk was consistently associated with higher incidence of fatal PCa in the entire cohort and higher PCa-specific mortality among cases. These findings add further evidence to suggest the potential role of dairy products in the development and prognosis of PCa.

Activation of Beta-Catenin Signaling in Androgen Receptor–Negative Prostate Cancer Cells

PubMed Central

Wan, Xinhai; Liu, Jie; Lu, Jing-Fang; Tzelepi, Vassiliki; Yang, Jun; Starbuck, Michael W.; Diao, Lixia; Wang, Jing; Efstathiou, Eleni; Vazquez, Elba S.; Troncoso, Patricia; Maity, Sankar N.; Navone, Nora M.

2012-01-01

Purpose To study Wnt/beta-catenin in castrate-resistant prostate cancer (CRPC) and understand its function independently of the beta-catenin–androgen receptor (AR) interaction. Experimental Design We performed beta-catenin immunocytochemical analysis, evaluated TOP-flash reporter activity (a reporter of beta-catenin–mediated transcription), and sequenced the beta-catenin gene in MDA PCa 118a, MDA PCa 118b, MDA PCa 2b, and PC-3 prostate cancer (PCa) cells. We knocked down beta-catenin in AR-negative MDA PCa 118b cells and performed comparative gene-array analysis. We also immunohistochemically analyzed beta-catenin and AR in 27 bone metastases of human CRPCs. Results Beta-catenin nuclear accumulation and TOP-flash reporter activity were high in MDA PCa 118b but not in MDA PCa 2b or PC-3 cells. MDA PCa 118a and 118b cells carry a mutated beta-catenin at codon 32 (D32G). Ten genes were expressed differently (false discovery rate, 0.05) in MDA PCa 118b cells with downregulated beta-catenin. One such gene, hyaluronan synthase 2 (HAS2), synthesizes hyaluronan, a core component of the extracellular matrix. We confirmed HAS2 upregulation in PC-3 cells transfected with D32G-mutant beta-catenin. Finally, we found nuclear localization of beta-catenin in 10 of 27 human tissue specimens; this localization was inversely associated with AR expression (P = 0.056, Fisher’s exact test), suggesting that reduced AR expression enables Wnt/beta-catenin signaling. Conclusion We identified a previously unknown downstream target of beta-catenin, HAS2, in PCa, and found that high beta-catenin nuclear localization and low or no AR expression may define a subpopulation of men with bone-metastatic PCa. These findings may guide physicians in managing these patients. PMID:22298898

Combinations of elevated tissue miRNA-17-92 cluster expression and serum prostate-specific antigen as potential diagnostic biomarkers for prostate cancer.

PubMed

Feng, Sujuan; Qian, Xiaosong; Li, Han; Zhang, Xiaodong

2017-12-01

The aim of the present study was to investigate the effectiveness of the miR-17-92 cluster as a disease progression marker in prostate cancer (PCa). Reverse transcription-quantitative polymerase chain reaction analysis was used to detect the microRNA (miR)-17-92 cluster expression levels in tissues from patients with PCa or benign prostatic hyperplasia (BPH), in addition to in PCa and BPH cell lines. Spearman correlation was used for comparison and estimation of correlations between miRNA expression levels and clinicopathological characteristics such as the Gleason score and prostate-specific antigen (PSA). Receiver operating curve (ROC) analysis was performed for evaluation of specificity and sensitivity of miR-17-92 cluster expression levels for discriminating patients with PCa from patients with BPH. Kaplan-Meier analysis was plotted to investigate the predictive potential of miR-17-92 cluster for PCa biochemical recurrence. Expression of the majority of miRNAs in the miR-17-92 cluster was identified to be significantly increased in PCa tissues and cell lines. Bivariate correlation analysis indicated that the high expression of unregulated miRNAs was positively correlated with Gleason grade, but had no significant association with PSA. ROC curves demonstrated that high expression of miR-17-92 cluster predicted a higher diagnostic accuracy compared with PSA. Improved discriminating quotients were observed when combinations of unregulated miRNAs with PSA were used. Survival analysis confirmed a high combined miRNA score of miR-17-92 cluster was associated with shorter biochemical recurrence interval. miR-17-92 cluster could be a potential diagnostic and prognostic biomarker for PCa, and the combination of the miR-17-92 cluster and serum PSA may enhance the accuracy for diagnosis of PCa.

A reversible Renilla luciferase protein complementation assay for rapid identification of protein–protein interactions reveals the existence of an interaction network involved in xyloglucan biosynthesis in the plant Golgi apparatus

PubMed Central

Lund, Christian H.; Bromley, Jennifer R.; Stenbæk, Anne; Rasmussen, Randi E.; Scheller, Henrik V.; Sakuragi, Yumiko

2015-01-01

A growing body of evidence suggests that protein–protein interactions (PPIs) occur amongst glycosyltransferases (GTs) required for plant glycan biosynthesis (e.g. cell wall polysaccharides and N-glycans) in the Golgi apparatus, and may control the functions of these enzymes. However, identification of PPIs in the endomembrane system in a relatively fast and simple fashion is technically challenging, hampering the progress in understanding the functional coordination of the enzymes in Golgi glycan biosynthesis. To solve the challenges, we adapted and streamlined a reversible Renilla luciferase protein complementation assay (Rluc-PCA), originally reported for use in human cells, for transient expression in Nicotiana benthamiana. We tested Rluc-PCA and successfully identified luminescence complementation amongst Golgi-localizing GTs known to form a heterodimer (GAUT1 and GAUT7) and those which homooligomerize (ARAD1). In contrast, no interaction was shown between negative controls (e.g. GAUT7, ARAD1, IRX9). Rluc-PCA was used to investigate PPIs amongst Golgi-localizing GTs involved in biosynthesis of hemicelluloses. Although no PPI was identified among six GTs involved in xylan biosynthesis, Rluc-PCA confirmed three previously proposed interactions and identified seven novel PPIs amongst GTs involved in xyloglucan biosynthesis. Notably, three of the novel PPIs were confirmed by a yeast-based split-ubiquitin assay. Finally, Gateway-enabled expression vectors were generated, allowing rapid construction of fusion proteins to the Rluc reporters and epitope tags. Our results show that Rluc-PCA coupled with transient expression in N. benthamiana is a fast and versatile method suitable for analysis of PPIs between Golgi resident proteins in an easy and mid-throughput fashion in planta. PMID:25326916

CAPE suppresses migration and invasion of prostate cancer cells via activation of non-canonical Wnt signaling.

PubMed

Tseng, Jen-Chih; Lin, Ching-Yu; Su, Liang-Chen; Fu, Hsiao-Hui; Yang, Shiaw-Der; Chuu, Chih-Pin

2016-06-21

Prostate cancer (PCa) was the fifth most common cancer overall in the world. More than 80% of patients died from PCa developed bone metastases. Caffeic acid phenethyl ester (CAPE) is a main bioactive component of honeybee hive propolis. Transwell and wound healing assays demonstrated that CAPE treatment suppressed the migration and invasion of PC-3 and DU-145 PCa cells. Gelatin zymography and Western blotting indicated that CAPE treatment reduced the abundance and activity of MMP-9 and MMP-2. Analysis using Micro-Western Array (MWA), a high-throughput antibody-based proteomics platform with 264 antibodies detecting signaling proteins involved in important pathways indicated that CAPE treatment induced receptor tyrosine kinase-like orphan receptor 2 (ROR2) in non-canonical Wnt signaling pathway but suppressed abundance of β-catenin, NF-κB activity, PI3K-Akt signaling, and epithelial-mesenchymal transition (EMT). Overexpression or knockdown of ROR2 suppressed or enhanced cell migration of PC-3 cells, respectively. TCF-LEF promoter binding assay revealed that CAPE treatment reduced canonical Wnt signaling. Intraperitoneal injection of CAPE reduced the metastasis of PC-3 xenografts in tail vein injection nude mice model. Immunohistochemical staining demonstrated that CAPE treatment increased abundance of ROR2 and Wnt5a but decreased protein expression of Ki67, Frizzle 4, NF-κB p65, MMP-9, Snail, β-catenin, and phosphorylation of IκBα. Clinical evidences suggested that genes affected by CAPE treatment (CTNNB1, RELA, FZD5, DVL3, MAPK9, SNAl1, ROR2, SMAD4, NFKBIA, DUSP6, and PLCB3) correlate with the aggressiveness of PCa. Our study suggested that CAPE may be a potential therapeutic agent for patients with advanced PCa.

A reversible Renilla luciferase protein complementation assay for rapid identification of protein-protein interactions reveals the existence of an interaction network involved in xyloglucan biosynthesis in the plant Golgi apparatus

DOE PAGES

Lund, C. H.; Bromley, J. R.; Stenbaek, A.; ...

2014-10-18

A growing body of evidence suggests that protein–protein interactions (PPIs) occur amongst glycosyltransferases (GTs) required for plant glycan biosynthesis (e.g. cell wall polysaccharides and N-glycans) in the Golgi apparatus, and may control the functions of these enzymes. However, identification of PPIs in the endomembrane system in a relatively fast and simple fashion is technically challenging, hampering the progress in understanding the functional coordination of the enzymes in Golgi glycan biosynthesis. To solve the challenges, we adapted and streamlined a reversible Renilla luciferase protein complementation assay (Rluc-PCA), originally reported for use in human cells, for transient expression in Nicotiana benthamiana. Wemore » tested Rluc-PCA and successfully identified luminescence complementation amongst Golgi-localizing GTs known to form a heterodimer (GAUT1 and GAUT7) and those which homooligomerize (ARAD1). In contrast, no interaction was shown between negative controls (e.g. GAUT7, ARAD1, IRX9). Rluc-PCA was used to investigate PPIs amongst Golgi-localizing GTs involved in biosynthesis of hemicelluloses. Although no PPI was identified among six GTs involved in xylan biosynthesis, Rluc-PCA confirmed three previously proposed interactions and identified seven novel PPIs amongst GTs involved in xyloglucan biosynthesis. Notably, three of the novel PPIs were confirmed by a yeast-based split-ubiquitin assay. Finally, Gateway-enabled expression vectors were generated, allowing rapid construction of fusion proteins to the Rluc reporters and epitope tags. In conclusion, our results show that Rluc-PCA coupled with transient expression in N. benthamiana is a fast and versatile method suitable for analysis of PPIs between Golgi resident proteins in an easy and mid-throughput fashion in planta.« less

ToF-SIMS and principal component analysis of lipids and amino acids from inflamed and dysplastic human colonic mucosa.

PubMed

Urbini, Marco; Petito, Valentina; de Notaristefani, Francesco; Scaldaferri, Franco; Gasbarrini, Antonio; Tortora, Luca

2017-10-01

Here, time of flight secondary ion mass spectrometry (ToF-SIMS) and multivariate analysis were combined to study the role of ulcerative colitis (UC), a type of inflammatory bowel disease (IBD), in the colon cancer progression. ToF-SIMS was used to obtain mass spectra and chemical maps from the mucosal surface of human normal (NC), inflamed (IC), and dysplastic (DC) colon tissues. Chemical mapping with a lateral resolution of ≈ 1 μm allowed to evaluate zonation of fatty acids and amino acids as well as the morphological condition of the intestinal glands. High mass resolution ToF-SIMS spectra showed chemical differences in lipid and amino acid composition as a function of pathological state. In positive ion mode, mono- (MAG), di- (DAG), and triacylglycerol (TAG) signals were detected in NC tissues, while in IC and DC tissues, the only cholesterol was present as lipid class representative. Signals from fatty acids, collected in negative ion mode, were subjected to principal component analysis (PCA). PCA showed a strict correlation between IC and DC samples, due to an increase of stearic, arachidonic, and linoleic acid. In the same way, differences in the amino acid composition were highlighted through multivariate analysis. PCA revealed that glutamic acid, leucine/isoleucine, and valine fragments are related to IC tissues. On the other hand, tyrosine, methionine, and tryptophan peaks contributed highly to the separation of DC tissues. Finally, a classification of NC, IC, and DC patients was also achieved through hierarchical cluster analysis of amino acid fragments. In this case, human colonic inflammation showed a stronger relationship with normal than dysplastic condition. Graphical Abstract ᅟ.

Linking Spatial Variations in Water Quality with Water and Land Management using Multivariate Techniques.

PubMed

Wan, Yongshan; Qian, Yun; Migliaccio, Kati White; Li, Yuncong; Conrad, Cecilia

2014-03-01

Most studies using multivariate techniques for pollution source evaluation are conducted in free-flowing rivers with distinct point and nonpoint sources. This study expanded on previous research to a managed "canal" system discharging into the Indian River Lagoon, Florida, where water and land management is the single most important anthropogenic factor influencing water quality. Hydrometric and land use data of four drainage basins were uniquely integrated into the analysis of 25 yr of monthly water quality data collected at seven stations to determine the impact of water and land management on the spatial variability of water quality. Cluster analysis (CA) classified seven monitoring stations into four groups (CA groups). All water quality parameters identified by discriminant analysis showed distinct spatial patterns among the four CA groups. Two-step principal component analysis/factor analysis (PCA/FA) was conducted with (i) water quality data alone and (ii) water quality data in conjunction with rainfall, flow, and land use data. The results indicated that PCA/FA of water quality data alone was unable to identify factors associated with management activities. The addition of hydrometric and land use data into PCA/FA revealed close associations of nutrients and color with land management and storm-water retention in pasture and citrus lands; total suspended solids, turbidity, and NO + NO with flow and Lake Okeechobee releases; specific conductivity with supplemental irrigation supply; and dissolved O with wetland preservation. The practical implication emphasizes the importance of basin-specific land and water management for ongoing pollutant loading reduction and ecosystem restoration programs. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

A novel-type phosphatidylinositol phosphate-interactive, Ca-binding protein PCaP1 in Arabidopsis thaliana: stable association with plasma membrane and partial involvement in stomata closure.

PubMed

Nagata, Chisako; Miwa, Chika; Tanaka, Natsuki; Kato, Mariko; Suito, Momoe; Tsuchihira, Ayako; Sato, Yori; Segami, Shoji; Maeshima, Masayoshi

2016-05-01

The Ca(2+)-binding protein-1 (PCaP1) of Arabidopsis thaliana is a new type protein that binds to phosphatidylinositol phosphates and Ca(2+)-calmodulin complex as well as free Ca(2+). Although biochemical properties, such as binding to ligands and N-myristoylation, have been revealed, the intracellular localization, tissue and cell specificity, integrity of membrane association and physiological roles of PCaP1 are unknown. We investigated the tissue and intracellular distribution of PCaP1 by using transgenic lines expressing PCaP1 linked with a green fluorescence protein (GFP) at the carboxyl terminus of PCaP1. GFP fluorescence was obviously detected in most tissues including root, stem, leaf and flower. In these tissues, PCaP1-GFP signal was observed predominantly in the plasma membrane even under physiological stress conditions but not in other organelles. The fluorescence was detected in the cytosol when the 25-residue N-terminal sequence was deleted from PCaP1 indicating essential contribution of N-myristoylation to the plasma membrane anchoring. Fluorescence intensity of PCaP1-GFP in roots was slightly decreased in seedlings grown in medium supplemented with high concentrations of iron for 1 week and increased in those grown with copper. In stomatal guard cells, PCaP1-GFP was strictly, specifically localized to the plasma membrane at the epidermal-cell side but not at the pore side. A T-DNA insertion mutant line of PCaP1 did not show marked phenotype in a life cycle except for well growth under high CO2 conditions. However, stomata of the mutant line did not close entirely even in high osmolarity, which usually induces stomata closure. These results suggest that PCaP1 is involved in the stomatal movement, especially closure process, in leaves and response to excessive copper in root and leaf as a mineral nutrient as a physiological role.

Principle component analysis (PCA) for investigation of relationship between population dynamics of microbial pathogenesis, chemical and sensory characteristics in beef slices containing Tarragon essential oil.

PubMed

Alizadeh Behbahani, Behrooz; Tabatabaei Yazdi, Farideh; Shahidi, Fakhri; Mortazavi, Seyed Ali; Mohebbi, Mohebbat

2017-04-01

Principle component analysis (PCA) was employed to examine the effect of the exerted treatments on the beef shelf life as well as discovering the correlations between the studied responses. Considering the variability of the dimensions of the responses, correlation coefficients were applied to form the matrix and extract the eigenvalue. Antimicrobial effect was evaluated on 10 pathogenic microorganisms through the methods of hole-plate diffusion method, disk diffusion method, pour plate method, minimum inhibitory concentration and minimum bactericidal/fungicidal concentration. Antioxidant potential and total phenolic content were examined through the method of 2,2-diphenyl-1-picrylhydrazyl (DPPH) and Folin-Ciocalteu method, respectively. The components were identified through gas chromatography and gas chromatography/mass spectrometry. Barhang seed mucilage (BSM) based edible coating containing 0, 0.5, 1 and 1.5% (w/w) Tarragon (T) essential oil mix were applied on beef slices to control the growth of pathogenic microorganisms. Microbiological (total viable count, psychrotrophic count, Escherichia coli, Staphylococcus aureus and fungi), chemical (thiobarbituric acid, peroxide value and pH) and sensory characteristics (odor, color and overall acceptability) analysis measurements were made during the storage periodically. PCA was employed to examine the effect of the exerted treatments on the beef shelf life as well as discovering the correlations between the studied responses. Considering the variability of the dimensions of the responses, correlation coefficients were applied to form the matrix and extract the eigenvalue. The PCA showed that the properties of the uncoated meat samples on the 9th, 12th, 15th and 18th days of storage are continuously changing independent of the exerted treatments on the other samples. This reveals the effect of the exerted treatments on the samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Morphometric evaluation of the knee in Chinese population reveals sexual dimorphism and age-related differences.

PubMed

Li, Ke; Cavaignac, Etienne; Xu, Wei; Cheng, Qiang; Telmon, Nobert; Huang, Wei

2018-02-20

Morphologic data of the knee is very important in the design of total knee prostheses. Generally, the designs of the total knee prostheses are based on the knee anatomy of Caucasian population. Moreover, in forensic medicine, a person's age and sex might be estimated by the shape of their knees. The aim of this study is to utilize three-dimensional morphometric analysis of the knee in Chinese population to reveal sexual dimorphism and age-related differences. Sexually dimorphic differences and age-related differences of the distal femur were studied by using geometric morphometric analysis of ten osteometric landmarks on three-dimensional reconstructions of 259 knees in Chinese population. General Procrustes analysis, PCA, and other discriminant analysis such as Mahalanobis and Goodall's F test were conducted for the knee to identify sexually dimorphism and age-related differences of the knee. The shape of distal femur between the male and female is significantly different. A difference between males and females in distal femur shape was identified by PCA; PC1 and PC2 accounted for 61.63% of the variance measured. The correct sex was assigned in 84.9% of cases by CVA, and the cross-validation revealed a 81.1% rate of correct sex estimation. The osteometric analysis also showed significant differences between the three age-related subgroups (< 40, 40-60, > 60 years, p < 0.005). This study showed both sex-related difference and age-related difference in the distal femur in Chinese population by 3D geometric morphometric analysis. Our bone measurements and geometric morphometric analysis suggest that population characteristics should be taken into account and may provide references for design of total knee prostheses in a Chinese population. Moreover, this reliable, accurate method could be used to perform diachronic and interethnic comparisons.

Analyzing coastal environments by means of functional data analysis

NASA Astrophysics Data System (ADS)

Sierra, Carlos; Flor-Blanco, Germán; Ordoñez, Celestino; Flor, Germán; Gallego, José R.

2017-07-01

Here we used Functional Data Analysis (FDA) to examine particle-size distributions (PSDs) in a beach/shallow marine sedimentary environment in Gijón Bay (NW Spain). The work involved both Functional Principal Components Analysis (FPCA) and Functional Cluster Analysis (FCA). The grainsize of the sand samples was characterized by means of laser dispersion spectroscopy. Within this framework, FPCA was used as a dimension reduction technique to explore and uncover patterns in grain-size frequency curves. This procedure proved useful to describe variability in the structure of the data set. Moreover, an alternative approach, FCA, was applied to identify clusters and to interpret their spatial distribution. Results obtained with this latter technique were compared with those obtained by means of two vector approaches that combine PCA with CA (Cluster Analysis). The first method, the point density function (PDF), was employed after adapting a log-normal distribution to each PSD and resuming each of the density functions by its mean, sorting, skewness and kurtosis. The second applied a centered-log-ratio (clr) to the original data. PCA was then applied to the transformed data, and finally CA to the retained principal component scores. The study revealed functional data analysis, specifically FPCA and FCA, as a suitable alternative with considerable advantages over traditional vector analysis techniques in sedimentary geology studies.

Predicting prostate biopsy outcome: prostate health index (phi) and prostate cancer antigen 3 (PCA3) are useful biomarkers.

PubMed

Ferro, Matteo; Bruzzese, Dario; Perdonà, Sisto; Mazzarella, Claudia; Marino, Ada; Sorrentino, Alessandra; Di Carlo, Angelina; Autorino, Riccardo; Di Lorenzo, Giuseppe; Buonerba, Carlo; Altieri, Vincenzo; Mariano, Angela; Macchia, Vincenzo; Terracciano, Daniela

2012-08-16

Indication for prostate biopsy is presently mainly based on prostate-specific antigen (PSA) serum levels and digital-rectal examination (DRE). In view of the unsatisfactory accuracy of these two diagnostic exams, research has focused on novel markers to improve pre-biopsy prostate cancer detection, such as phi and PCA3. The purpose of this prospective study was to assess the diagnostic accuracy of phi and PCA3 for prostate cancer using biopsy as gold standard. Phi index (Beckman coulter immunoassay), PCA3 score (Progensa PCA3 assay) and other established biomarkers (tPSA, fPSA and %fPSA) were assessed before a 18-core prostate biopsy in a group of 251 subjects at their first biopsy. Values of %p2PSA and phi were significantly higher in patients with PCa compared with PCa-negative group (p<0.001) and also compared with high grade prostatic intraepithelial neoplasia (HGPIN) (p<0.001). PCA3 score values were significantly higher in PCa compared with PCa-negative subjects (p<0.001) and in HGPIN vs PCa-negative patients (p<0.001). ROC curve analysis showed that %p2PSA, phi and PCA3 are predictive of malignancy. In conclusion, %p2PSA, phi and PCA3 may predict a diagnosis of PCa in men undergoing their first prostate biopsy. PCA3 score is more useful in discriminating between HGPIN and non-cancer. Copyright © 2012 Elsevier B.V. All rights reserved.

PCA as a practical indicator of OPLS-DA model reliability.

PubMed

Worley, Bradley; Powers, Robert

Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) are powerful statistical modeling tools that provide insights into separations between experimental groups based on high-dimensional spectral measurements from NMR, MS or other analytical instrumentation. However, when used without validation, these tools may lead investigators to statistically unreliable conclusions. This danger is especially real for Partial Least Squares (PLS) and OPLS, which aggressively force separations between experimental groups. As a result, OPLS-DA is often used as an alternative method when PCA fails to expose group separation, but this practice is highly dangerous. Without rigorous validation, OPLS-DA can easily yield statistically unreliable group separation. A Monte Carlo analysis of PCA group separations and OPLS-DA cross-validation metrics was performed on NMR datasets with statistically significant separations in scores-space. A linearly increasing amount of Gaussian noise was added to each data matrix followed by the construction and validation of PCA and OPLS-DA models. With increasing added noise, the PCA scores-space distance between groups rapidly decreased and the OPLS-DA cross-validation statistics simultaneously deteriorated. A decrease in correlation between the estimated loadings (added noise) and the true (original) loadings was also observed. While the validity of the OPLS-DA model diminished with increasing added noise, the group separation in scores-space remained basically unaffected. Supported by the results of Monte Carlo analyses of PCA group separations and OPLS-DA cross-validation metrics, we provide practical guidelines and cross-validatory recommendations for reliable inference from PCA and OPLS-DA models.

ToF-SIMS PCA analysis of Myrtus communis L.

NASA Astrophysics Data System (ADS)

Piras, F. M.; Dettori, M. F.; Magnani, A.

2009-06-01

Nowadays there is a growing interest of researchers for the application of sophisticated analytical techniques in conjunction with statistical data analysis methods to the characterization of natural products to assure their authenticity and quality, and for the possibility of direct analysis of food to obtain maximum information. In this work, time-of-flight secondary ion mass spectrometry (ToF-SIMS) in conjunction with principal components analysis (PCA) are applied to study the chemical composition and variability of Sardinian myrtle ( Myrtus communis L.) through the analysis of both berries alcoholic extracts and berries epicarp. ToF-SIMS spectra of berries epicarp show that the epicuticular waxes consist mainly of carboxylic acids with chain length ranging from C20 to C30, or identical species formed from fragmentation of long-chain esters. PCA of ToF-SIMS data from myrtle berries epicarp distinguishes two groups characterized by a different surface concentration of triacontanoic acid. Variability in antocyanins, flavonols, α-tocopherol, and myrtucommulone contents is showed by ToF-SIMS PCA analysis of myrtle berries alcoholic extracts.

ICI 182,780-regulated gene expression in DU145 prostate cancer cells is mediated by estrogen receptor-beta/NFkappaB crosstalk.

PubMed

Leung, Yuet-Kin; Gao, Ying; Lau, Kin-Mang; Zhang, Xiang; Ho, Shuk-Mei

2006-04-01

Estrogen receptor (ER)-beta is the predominant ER subtype in prostate cancer (PCa). We previously demonstrated that ICI 182,780 (ICI), but not estrogens, exerted dose-dependent growth inhibition on DU145 PCa cells by an ER-beta-mediated pathway. Transcriptional profiling detected a greater than three-fold upregulation of seven genes after a 12-hour exposure to 1 microM ICI. Semiquantitative reverse transcriptase polymerase chain reaction confirmed the upregulation of four genes by ICI: interleukin-12alpha chain, interleukin-8, embryonic growth/differentiation factor, and RYK tyrosine kinase. Treatment with an ER-beta antisense oligonucleotide reduced cellular ER-beta mRNA and induced loss of expression of these genes. Sequence analysis revealed the presence of consensus NFkappaB sites, but not estrogen-responsive elements, in promoters of all four genes. Reporter assay and chromatin immunoprecipitation experiments demonstrated that ICI-induced gene expression could be mediated by crosstalk between ER-beta and the NFkappaB signaling pathway, denoting a novel mechanism of ER-beta-mediated ICI action. Therefore, combined therapies targeting ER-beta and NFkappaB signaling may be synergistic as treatment for PCa.

ICI 182,780-Regulated Gene Expression in DU145 Prostate Cancer Cells Is Mediated by Estrogen Receptor-β/NFκB Crosstalk1

PubMed Central

Leung, Yuet-Kin; Gao, Ying; Lau, Kin-Mang; Zhang, Xiang; Ho, Shuk-Mei

2006-01-01

Abstract Estrogen receptor (ER)-β is the predominant ER subtype in prostate cancer (PCa). We previously demonstrated that ICI 182,780 (ICI), but not estrogens, exerted dose-dependent growth inhibition on DU145 PCa cells by an ER-β-mediated pathway. Transcriptional profiling detected a greater than three-fold upregulation of seven genes after a 12-hour exposure to 1 µM ICI. Semi-quantitative reverse transcriptase polymerase chain reaction confirmed the upregulation of four genes by ICI: interleukin-12α chain, interleukin-8, embryonic growth/differentiation factor, and RYK tyrosine kinase. Treatment with an ER-β antisense oligonucleotide reduced cellular ER-β mRNA and induced loss of expression of these genes. Sequence analysis revealed the presence of consensus NFκB sites, but not estrogen-responsive elements, in promoters of all four genes. Reporter assay and chromatin immunoprecipitation experiments demonstrated that ICI-induced gene expression could be mediated by crosstalk between ER-α and the NFκB signaling pathway, denoting a novel mechanism of ER-β-mediated ICI action. Therefore, combined therapies targeting ER-β and NFκB signaling may be synergistic as treatment for PCa. PMID:16756716

Discrimination of complex mixtures by a colorimetric sensor array: coffee aromas.

PubMed

Suslick, Benjamin A; Feng, Liang; Suslick, Kenneth S

2010-03-01

The analysis of complex mixtures presents a difficult challenge even for modern analytical techniques, and the ability to discriminate among closely similar such mixtures often remains problematic. Coffee provides a readily available archetype of such highly multicomponent systems. The use of a low-cost, sensitive colorimetric sensor array for the detection and identification of coffee aromas is reported. The color changes of the sensor array were used as a digital representation of the array response and analyzed with standard statistical methods, including principal component analysis (PCA) and hierarchical clustering analysis (HCA). PCA revealed that the sensor array has exceptionally high dimensionality with 18 dimensions required to define 90% of the total variance. In quintuplicate runs of 10 commercial coffees and controls, no confusions or errors in classification by HCA were observed in 55 trials. In addition, the effects of temperature and time in the roasting of green coffee beans were readily observed and distinguishable with a resolution better than 10 degrees C and 5 min, respectively. Colorimetric sensor arrays demonstrate excellent potential for complex systems analysis in real-world applications and provide a novel method for discrimination among closely similar complex mixtures.

Analysis of differences between Western and East-Asian faces based on facial region segmentation and PCA for facial expression recognition

NASA Astrophysics Data System (ADS)

Benitez-Garcia, Gibran; Nakamura, Tomoaki; Kaneko, Masahide

2017-01-01

Darwin was the first one to assert that facial expressions are innate and universal, which are recognized across all cultures. However, recent some cross-cultural studies have questioned this assumed universality. Therefore, this paper presents an analysis of the differences between Western and East-Asian faces of the six basic expressions (anger, disgust, fear, happiness, sadness and surprise) focused on three individual facial regions of eyes-eyebrows, nose and mouth. The analysis is conducted by applying PCA for two feature extraction methods: appearance-based by using the pixel intensities of facial parts, and geometric-based by handling 125 feature points from the face. Both methods are evaluated using 4 standard databases for both racial groups and the results are compared with a cross-cultural human study applied to 20 participants. Our analysis reveals that differences between Westerns and East-Asians exist mainly on the regions of eyes-eyebrows and mouth for expressions of fear and disgust respectively. This work presents important findings for a better design of automatic facial expression recognition systems based on the difference between two racial groups.

NMR-Based Metabolomic Study on Isatis tinctoria: Comparison of Different Accessions, Harvesting Dates, and the Effect of Repeated Harvesting.

PubMed

Guldbrandsen, Niels; Kostidis, Sarantos; Schäfer, Hartmut; De Mieri, Maria; Spraul, Manfred; Skaltsounis, Alexios-Leandros; Mikros, Emmanuel; Hamburger, Matthias

2015-05-22

Isatis tinctoria is an ancient dye and medicinal plant with potent anti-inflammatory and antiallergic properties. Metabolic differences were investigated by NMR spectroscopy of accessions from different origins that were grown under identical conditions on experimental plots. For these accessions, metabolite profiles at different harvesting dates were analyzed, and single and repeatedly harvested plants were compared. Leaf samples were shock-frozen in liquid N2 immediately after being harvested, freeze-dried, and cryomilled prior to extraction. Extracts were prepared by pressurized liquid extraction with ethyl acetate and 70% aqueous methanol. NMR spectra were analyzed using a combination of different methods of multivariate data analysis such as principal component analysis (PCA), canonical analysis (CA), and k-nearest neighbor concept (k-NN). Accessions and harvesting dates were well separated in the PCA/CA/k-NN analysis in both extracts. Pairwise statistical total correlation spectroscopy (STOCSY) revealed unsaturated fatty acids, porphyrins, carbohydrates, indole derivatives, isoprenoids, phenylpropanoids, and minor aromatic compounds as the cause of these differences. In addition, the metabolite profile was affected by the repeated harvest regime, causing a decrease of 1,5-anhydroglucitol, sucrose, unsaturated fatty acids, porphyrins, isoprenoids, and a flavonoid.

Discrimination of Complex Mixtures by a Colorimetric Sensor Array: Coffee Aromas

PubMed Central

Suslick, Benjamin A.; Feng, Liang; Suslick, Kenneth S.

2010-01-01

The analysis of complex mixtures presents a difficult challenge even for modern analytical techniques, and the ability to discriminate among closely similar such mixtures often remains problematic. Coffee provides a readily available archetype of such highly multicomponent systems. The use of a low-cost, sensitive colorimetric sensor array for the detection and identification of coffee aromas is reported. The color changes of the sensor array were used as a digital representation of the array response and analyzed with standard statistical methods, including principal component analysis (PCA) and hierarchical clustering analysis (HCA). PCA revealed that the sensor array has exceptionally high dimensionality with 18 dimensions required to define 90% of the total variance. In quintuplicate runs of 10 commercial coffees and controls, no confusions or errors in classification by HCA were observed in 55 trials. In addition, the effects of temperature and time in the roasting of green coffee beans were readily observed and distinguishable with a resolution better than 10 °C and 5 min, respectively. Colorimetric sensor arrays demonstrate excellent potential for complex systems analysis in real-world applications and provide a novel method for discrimination among closely similar complex mixtures. PMID:20143838

Adaptive online monitoring for ICU patients by combining just-in-time learning and principal component analysis.

PubMed

Li, Xuejian; Wang, Youqing

2016-12-01

Offline general-type models are widely used for patients' monitoring in intensive care units (ICUs), which are developed by using past collected datasets consisting of thousands of patients. However, these models may fail to adapt to the changing states of ICU patients. Thus, to be more robust and effective, the monitoring models should be adaptable to individual patients. A novel combination of just-in-time learning (JITL) and principal component analysis (PCA), referred to learning-type PCA (L-PCA), was proposed for adaptive online monitoring of patients in ICUs. JITL was used to gather the most relevant data samples for adaptive modeling of complex physiological processes. PCA was used to build an online individual-type model and calculate monitoring statistics, and then to judge whether the patient's status is normal or not. The adaptability of L-PCA lies in the usage of individual data and the continuous updating of the training dataset. Twelve subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and five vital signs of each subject were chosen. The proposed method was compared with the traditional PCA and fast moving-window PCA (Fast MWPCA). The experimental results demonstrated that the fault detection rates respectively increased by 20 % and 47 % compared with PCA and Fast MWPCA. L-PCA is first introduced into ICU patients monitoring and achieves the best monitoring performance in terms of adaptability to changes in patient status and sensitivity for abnormality detection.

Experimental Researches on the Durability Indicators and the Physiological Comfort of Fabrics using the Principal Component Analysis (PCA) Method

NASA Astrophysics Data System (ADS)

Hristian, L.; Ostafe, M. M.; Manea, L. R.; Apostol, L. L.

2017-06-01

The work pursued the distribution of combed wool fabrics destined to manufacturing of external articles of clothing in terms of the values of durability and physiological comfort indices, using the mathematical model of Principal Component Analysis (PCA). Principal Components Analysis (PCA) applied in this study is a descriptive method of the multivariate analysis/multi-dimensional data, and aims to reduce, under control, the number of variables (columns) of the matrix data as much as possible to two or three. Therefore, based on the information about each group/assortment of fabrics, it is desired that, instead of nine inter-correlated variables, to have only two or three new variables called components. The PCA target is to extract the smallest number of components which recover the most of the total information contained in the initial data.

Molecular analysis of bacterial microbiota associated with oysters (Crassostrea gigas and Crassostrea corteziensis) in different growth phases at two cultivation sites.

PubMed

Trabal, Natalia; Mazón-Suástegui, José M; Vázquez-Juárez, Ricardo; Asencio-Valle, Felipe; Morales-Bojórquez, Enrique; Romero, Jaime

2012-08-01

Microbiota presumably plays an essential role in inhibiting pathogen colonization and in the maintenance of health in oysters, but limited data exist concerning their different growth phases and conditions. We analyzed the bacterial microbiota composition of two commercial oysters: Crassostrea gigas and Crassostrea corteziensis. Differences in microbiota were assayed in three growth phases: post-larvae at the hatchery, juvenile, and adult at two grow-out cultivation sites. Variations in the microbiota were assessed by PCR analysis of the 16S rRNA gene in DNA extracted from depurated oysters. Restriction fragment length polymorphism (RFLP) profiles were studied using Dice's similarity coefficient (Cs) and statistical principal component analysis (PCA). The microbiota composition was determined by sequencing temperature gradient gel electrophoresis (TGGE) bands. The RFLP analysis of post-larvae revealed homology in the microbiota of both oyster species (Cs > 88 %). Dice and PCA analyses of C. corteziensis but not C. gigas showed differences in the microbiota according to the cultivation sites. The sequencing analysis revealed low bacterial diversity (primarily β-Proteobacteria, Firmicutes, and Spirochaetes), with Burkholderia cepacia being the most abundant bacteria in both oyster species. This study provides the first description of the microbiota in C. corteziensis, which was shown to be influenced by cultivation site conditions. During early growth, we observed that B. cepacia colonized and remained strongly associated with the two oysters, probably in a symbiotic host-bacteria relationship. This association was maintained in the three growth phases and was not altered by environmental conditions or the management of the oysters at the grow-out site.

EMPCA and Cluster Analysis of Quasar Spectra: Construction and Application to Simulated Spectra

NASA Astrophysics Data System (ADS)

Marrs, Adam; Leighly, Karen; Wagner, Cassidy; Macinnis, Francis

2017-01-01

Quasars have complex spectra with emission lines influenced by many factors. Therefore, to fully describe the spectrum requires specification of a large number of parameters, such as line equivalent width, blueshift, and ratios. Principal Component Analysis (PCA) aims to construct eigenvectors-or principal components-from the data with the goal of finding a few key parameters that can be used to predict the rest of the spectrum fairly well. Analysis of simulated quasar spectra was used to verify and justify our modified application of PCA.We used a variant of PCA called Weighted Expectation Maximization PCA (EMPCA; Bailey 2012) along with k-means cluster analysis to analyze simulated quasar spectra. Our approach combines both analytical methods to address two known problems with classical PCA. EMPCA uses weights to account for uncertainty and missing points in the spectra. K-means groups similar spectra together to address the nonlinearity of quasar spectra, specifically variance in blueshifts and widths of the emission lines.In producing and analyzing simulations, we first tested the effects of varying equivalent widths and blueshifts on the derived principal components, and explored the differences between standard PCA and EMPCA. We also tested the effects of varying signal-to-noise ratio. Next we used the results of fits to composite quasar spectra (see accompanying poster by Wagner et al.) to construct a set of realistic simulated spectra, and subjected those spectra to the EMPCA /k-means analysis. We concluded that our approach was validated when we found that the mean spectra from our k-means clusters derived from PCA projection coefficients reproduced the trends observed in the composite spectra.Furthermore, our method needed only two eigenvectors to identify both sets of correlations used to construct the simulations, as well as indicating the linear and nonlinear segments. Comparing this to regular PCA, which can require a dozen or more components, or to direct spectral analysis that may need measurement of 20 fit parameters, shows why the dual application of these two techniques is such a powerful tool.

Sarcosine Up-Regulates Expression of Genes Involved in Cell Cycle Progression of Metastatic Models of Prostate Cancer

PubMed Central

Heger, Zbynek; Merlos Rodrigo, Miguel Angel; Michalek, Petr; Polanska, Hana; Masarik, Michal; Vit, Vitezslav; Plevova, Mariana; Pacik, Dalibor; Eckschlager, Tomas; Stiborova, Marie

2016-01-01

The effects of sarcosine on the processes driving prostate cancer (PCa) development remain still unclear. Herein, we show that a supplementation of metastatic PCa cells (androgen independent PC-3 and androgen dependent LNCaP) with sarcosine stimulates cells proliferation in vitro. Similar stimulatory effects were observed also in PCa murine xenografts, in which sarcosine treatment induced a tumor growth and significantly reduced weight of treated mice (p < 0.05). Determination of sarcosine metabolism-related amino acids and enzymes within tumor mass revealed significantly increased glycine, serine and sarcosine concentrations after treatment accompanied with the increased amount of sarcosine dehydrogenase. In both tumor types, dimethylglycine and glycine-N-methyltransferase were affected slightly, only. To identify the effects of sarcosine treatment on the expression of genes involved in any aspect of cancer development, we further investigated expression profiles of excised tumors using cDNA electrochemical microarray followed by validation using the semi-quantitative PCR. We found 25 differentially expressed genes in PC-3, 32 in LNCaP tumors and 18 overlapping genes. Bioinformatical processing revealed strong sarcosine-related induction of genes involved particularly in a cell cycle progression. Our exploratory study demonstrates that sarcosine stimulates PCa metastatic cells irrespectively of androgen dependence. Overall, the obtained data provides valuable information towards understanding the role of sarcosine in PCa progression and adds another piece of puzzle into a picture of sarcosine oncometabolic potential. PMID:27824899

Age-related changes in rat intrinsic laryngeal muscles: analysis of muscle fibers, muscle fiber proteins, and subneural apparatuses.

PubMed

Nishida, Naoya; Taguchi, Aki; Motoyoshi, Kazumi; Hyodo, Masamitsu; Gyo, Kiyofumi; Desaki, Junzo

2013-03-01

We compared age-related changes in the intrinsic laryngeal muscles of aged and young adult rats by determining the number and diameter of muscle fibers, contractile muscle protein (myosin heavy chain isoforms, MHC) composition, and the morphology of the subneural apparatuses. In aged rats, both the numbers and the diameters of muscle fibers decreased in the cricothyroid (CT) muscle. The number of fibers, but not diameter, decreased in the thyroarytenoid (TA) muscle. In the posterior cricoarytenoid (PCA) muscle, neither the number nor the diameter of fibers changed significantly. Aging was associated with a decrease in type IIB and an increase in type IIA MHC isoform levels in CT muscle, but no such changes were observed in the TA or PCA muscles. Morphological examination of primary synaptic clefts of the subneural apparatus revealed that aging resulted in decreased labyrinthine and increased depression types in only the CT muscle. In the aged group, morphologically immature subneural apparatuses were found infrequently in the CT muscle, indicating continued tissue remodeling. We suggest, therefore, that age-related changes in the intrinsic laryngeal muscles primarily involve the CT muscle, whereas the structures of the TA and PCA muscles may better resist aging processes and therefore are less vulnerable to functional impairment. This may reflect differences in their roles; the CT muscle controls the tone of the vocal folds, while the TA and PCA muscles play an essential role in vital activities such as respiration and swallowing.

AKT-mediated stabilization of histone methyltransferase WHSC1 promotes prostate cancer metastasis

PubMed Central

Li, Ni; Xue, Wei; Yuan, Huairui; Dong, Baijun; Ding, Yufeng; Liu, Yongfeng; Jiang, Min; Kan, Shan; Sun, Tongyu; Ren, Jiale; Pan, Qiang; Li, Xiang; Zhang, Peiyuan; Wang, Yan; Wang, Xiaoming; Li, Qintong

2017-01-01

Loss of phosphatase and tensin homolog (PTEN) and activation of the PI3K/AKT signaling pathway are hallmarks of prostate cancer (PCa). However, these alterations alone are insufficient for cells to acquire metastatic traits. Here, we have shown that the histone dimethyl transferase WHSC1 critically drives indolent PTEN-null tumors to become metastatic PCa. In a PTEN-null murine PCa model, WHSC1 overexpression in prostate epithelium cooperated with Pten deletion to produce a metastasis-prone tumor. Conversely, genetic ablation of Whsc1 prevented tumor progression in PTEN-null mice. Molecular characterization revealed that increased AKT activity due to PTEN loss directly phosphorylates WHSC1 at S172, preventing WHSC1 degradation by CRL4Cdt2 E3 ligase. Increased WHSC1 expression transcriptionally upregulates expression of RICTOR, a pivotal component of mTOR complex 2 (mTORC2), to further enhance AKT activity. Therefore, the AKT/WHSC1/mTORC2 signaling cascade represents a vicious feedback loop that elicits unrestrained AKT signaling. Furthermore, we determined that WHSC1 positively regulates Rac1 transcription to increase tumor cell motility. The biological importance of a WHSC1-mediated signaling cascade is substantiated by patient sample analysis in which WHSC1 signaling is tightly correlated with disease progression and recurrence. Taken together, our findings highlight a pivotal link between an epigenetic regulator, WHSC1, and key intracellular signaling molecules, AKT, RICTOR, and Rac1, to drive PCa metastasis. PMID:28319045

Effect of process control agent on the porous structure and mechanical properties of a biomedical Ti-Sn-Nb alloy produced by powder metallurgy.

PubMed

Nouri, A; Hodgson, P D; Wen, C E

2010-04-01

The influence of different amounts and types of process control agent (PCA), i.e., stearic acid and ethylene bis-stearamide, on the porous structure and mechanical properties of a biomedical Ti-16Sn-4Nb (wt.%) alloy was investigated. Alloy synthesis was performed on elemental metal powders using high-energy ball milling for 5h. Results indicated that varying the PCA content during ball milling led to a drastic change in morphology and particle-size distribution of the ball-milled powders. Porous titanium alloy samples sintered from the powders ball milled with the addition of various amounts of PCA also revealed different pore morphology and porosity. The Vickers hardness of the sintered titanium alloy samples exhibited a considerable increase with increasing PCA content. Moreover, the addition of larger amounts of PCA in the powder mixture resulted in a significant increase in the elastic modulus and peak stress for the sintered porous titanium alloy samples under compression. It should also be mentioned that the addition of PCA introduced contamination (mainly carbon and oxygen) into the sintered porous product. Crown Copyright 2009. Published by Elsevier Ltd. All rights reserved.

A better understanding of long-range temporal dependence of traffic flow time series

NASA Astrophysics Data System (ADS)

Feng, Shuo; Wang, Xingmin; Sun, Haowei; Zhang, Yi; Li, Li

2018-02-01

Long-range temporal dependence is an important research perspective for modelling of traffic flow time series. Various methods have been proposed to depict the long-range temporal dependence, including autocorrelation function analysis, spectral analysis and fractal analysis. However, few researches have studied the daily temporal dependence (i.e. the similarity between different daily traffic flow time series), which can help us better understand the long-range temporal dependence, such as the origin of crossover phenomenon. Moreover, considering both types of dependence contributes to establishing more accurate model and depicting the properties of traffic flow time series. In this paper, we study the properties of daily temporal dependence by simple average method and Principal Component Analysis (PCA) based method. Meanwhile, we also study the long-range temporal dependence by Detrended Fluctuation Analysis (DFA) and Multifractal Detrended Fluctuation Analysis (MFDFA). The results show that both the daily and long-range temporal dependence exert considerable influence on the traffic flow series. The DFA results reveal that the daily temporal dependence creates crossover phenomenon when estimating the Hurst exponent which depicts the long-range temporal dependence. Furthermore, through the comparison of the DFA test, PCA-based method turns out to be a better method to extract the daily temporal dependence especially when the difference between days is significant.

Proteomic and computational analysis of bronchoalveolar proteins during the course of the acute respiratory distress syndrome.

PubMed

Chang, Dong W; Hayashi, Shinichi; Gharib, Sina A; Vaisar, Tomas; King, S Trevor; Tsuchiya, Mitsuhiro; Ruzinski, John T; Park, David R; Matute-Bello, Gustavo; Wurfel, Mark M; Bumgarner, Roger; Heinecke, Jay W; Martin, Thomas R

2008-10-01

Acute lung injury causes complex changes in protein expression in the lungs. Whereas most prior studies focused on single proteins, newer methods allowing the simultaneous study of many proteins could lead to a better understanding of pathogenesis and new targets for treatment. The purpose of this study was to examine the changes in protein expression in the bronchoalveolar lavage fluid (BALF) of patients during the course of the acute respiratory distress syndrome (ARDS). Using two-dimensional difference gel electrophoresis (DIGE), the expression of proteins in the BALF from patients on Days 1 (n = 7), 3 (n = 8), and 7 (n = 5) of ARDS were compared with findings in normal volunteers (n = 9). The patterns of protein expression were analyzed using principal component analysis (PCA). Biological processes that were enriched in the BALF proteins of patients with ARDS were identified using Gene Ontology (GO) analysis. Protein networks that model the protein interactions in the BALF were generated using Ingenuity Pathway Analysis. An average of 991 protein spots were detected using DIGE. Of these, 80 protein spots, representing 37 unique proteins in all of the fluids, were identified using mass spectrometry. PCA confirmed important differences between the proteins in the ARDS and normal samples. GO analysis showed that these differences are due to the enrichment of proteins involved in inflammation, infection, and injury. The protein network analysis showed that the protein interactions in ARDS are complex and redundant, and revealed unexpected central components in the protein networks. Proteomics and protein network analysis reveals the complex nature of lung protein interactions in ARDS. The results provide new insights about protein networks in injured lungs, and identify novel mediators that are likely to be involved in the pathogenesis and progression of acute lung injury.

Free energy landscape of a biomolecule in dihedral principal component space: sampling convergence and correspondence between structures and minima.

PubMed

Maisuradze, Gia G; Leitner, David M

2007-05-15

Dihedral principal component analysis (dPCA) has recently been developed and shown to display complex features of the free energy landscape of a biomolecule that may be absent in the free energy landscape plotted in principal component space due to mixing of internal and overall rotational motion that can occur in principal component analysis (PCA) [Mu et al., Proteins: Struct Funct Bioinfo 2005;58:45-52]. Another difficulty in the implementation of PCA is sampling convergence, which we address here for both dPCA and PCA using a tetrapeptide as an example. We find that for both methods the sampling convergence can be reached over a similar time. Minima in the free energy landscape in the space of the two largest dihedral principal components often correspond to unique structures, though we also find some distinct minima to correspond to the same structure. 2007 Wiley-Liss, Inc.

Detecting phase separation of freeze-dried binary amorphous systems using pair-wise distribution function and multivariate data analysis.

PubMed

Chieng, Norman; Trnka, Hjalte; Boetker, Johan; Pikal, Michael; Rantanen, Jukka; Grohganz, Holger

2013-09-15

The purpose of this study is to investigate the use of multivariate data analysis for powder X-ray diffraction-pair-wise distribution function (PXRD-PDF) data to detect phase separation in freeze-dried binary amorphous systems. Polymer-polymer and polymer-sugar binary systems at various ratios were freeze-dried. All samples were analyzed by PXRD, transformed to PDF and analyzed by principal component analysis (PCA). These results were validated by differential scanning calorimetry (DSC) through characterization of glass transition of the maximally freeze-concentrate solute (Tg'). Analysis of PXRD-PDF data using PCA provides a more clear 'miscible' or 'phase separated' interpretation through the distribution pattern of samples on a score plot presentation compared to residual plot method. In a phase separated system, samples were found to be evenly distributed around the theoretical PDF profile. For systems that were miscible, a clear deviation of samples away from the theoretical PDF profile was observed. Moreover, PCA analysis allows simultaneous analysis of replicate samples. Comparatively, the phase behavior analysis from PXRD-PDF-PCA method was in agreement with the DSC results. Overall, the combined PXRD-PDF-PCA approach improves the clarity of the PXRD-PDF results and can be used as an alternative explorative data analytical tool in detecting phase separation in freeze-dried binary amorphous systems. Copyright © 2013 Elsevier B.V. All rights reserved.

24 CFR 401.451 - PAE Physical Condition Analysis (PCA).

Code of Federal Regulations, 2010 CFR

2010-04-01

... PROGRAM (MARK-TO-MARKET) Restructuring Plan § 401.451 PAE Physical Condition Analysis (PCA). (a) Review and certification of owner evaluation. (1) The PAE must independently evaluate the physical condition... 24 Housing and Urban Development 2 2010-04-01 2010-04-01 false PAE Physical Condition Analysis...

24 CFR 401.451 - PAE Physical Condition Analysis (PCA).

Code of Federal Regulations, 2013 CFR

2013-04-01

... 24 Housing and Urban Development 2 2013-04-01 2013-04-01 false PAE Physical Condition Analysis... PROGRAM (MARK-TO-MARKET) Restructuring Plan § 401.451 PAE Physical Condition Analysis (PCA). (a) Review and certification of owner evaluation. (1) The PAE must independently evaluate the physical condition...

24 CFR 401.451 - PAE Physical Condition Analysis (PCA).

Code of Federal Regulations, 2011 CFR

2011-04-01

... 24 Housing and Urban Development 2 2011-04-01 2011-04-01 false PAE Physical Condition Analysis... PROGRAM (MARK-TO-MARKET) Restructuring Plan § 401.451 PAE Physical Condition Analysis (PCA). (a) Review and certification of owner evaluation. (1) The PAE must independently evaluate the physical condition...

24 CFR 401.451 - PAE Physical Condition Analysis (PCA).

Code of Federal Regulations, 2012 CFR

2012-04-01

... 24 Housing and Urban Development 2 2012-04-01 2012-04-01 false PAE Physical Condition Analysis... PROGRAM (MARK-TO-MARKET) Restructuring Plan § 401.451 PAE Physical Condition Analysis (PCA). (a) Review and certification of owner evaluation. (1) The PAE must independently evaluate the physical condition...

24 CFR 401.451 - PAE Physical Condition Analysis (PCA).

Code of Federal Regulations, 2014 CFR

2014-04-01

... 24 Housing and Urban Development 2 2014-04-01 2014-04-01 false PAE Physical Condition Analysis... PROGRAM (MARK-TO-MARKET) Restructuring Plan § 401.451 PAE Physical Condition Analysis (PCA). (a) Review and certification of owner evaluation. (1) The PAE must independently evaluate the physical condition...

Physical activity in relation to risk of prostate cancer: a systematic review and meta-analysis.

PubMed

Benke, I N; Leitzmann, M F; Behrens, G; Schmid, D

2018-05-01

Prostate cancer (PCa) is one of the most common cancers among men, yet little is known about its modifiable risk and protective factors. This study aims to quantitatively summarize observational studies relating physical activity (PA) to PCa incidence and mortality. Published articles pertaining to PA and PCa incidence and mortality were retrieved in July 2017 using the Medline and EMBASE databases. The literature review yielded 48 cohort studies and 24 case-control studies with a total of 151 748 PCa cases. The mean age of the study participants at baseline was 61 years. In random-effects models, comparing the highest versus the lowest level of overall PA showed a summary relative risk (RR) estimate for total PCa incidence close to the null [RR = 0.99, 95% confidence interval (CI) = 0.94-1.04]. The corresponding RRs for advanced and non-advanced PCa were 0.92 (95% CI = 0.80-1.06) and 0.95 (95% CI = 0.85-1.07), respectively. We noted a statistically significant inverse association between long-term occupational activity and total PCa (RR = 0.83, 95% CI = 0.71-0.98, n studies = 13), although that finding became statistically non-significant when individual studies were removed from the analysis. When evaluated by cancer subtype, an inverse association with long-term occupational activity was noted for non-advanced/non-aggressive PCa (RR = 0.51, 95% CI = 0.37-0.71, n studies = 2) and regular recreational activity was inversely related to advanced/aggressive PCa (RR = 0.75, 95% CI = 0.60-0.95, n studies = 2), although these observations are based on a low number of studies. Moreover, PA after diagnosis was related to reduced risk of PCa mortality among survivors of PCa (summary RR based on four studies = 0.69, 95% CI = 0.55-0.85). Whether PA protects against PCa remains elusive. Further investigation taking into account the complex clinical and pathologic nature of PCa is needed to clarify the PA and PCa incidence relation. Moreover, future studies are needed to confirm whether PA after diagnosis reduces risk of PCa mortality.

Cluster and principal component analysis based on SSR markers of Amomum tsao-ko in Jinping County of Yunnan Province

NASA Astrophysics Data System (ADS)

Ma, Mengli; Lei, En; Meng, Hengling; Wang, Tiantao; Xie, Linyan; Shen, Dong; Xianwang, Zhou; Lu, Bingyue

2017-08-01

Amomum tsao-ko is a commercial plant that used for various purposes in medicinal and food industries. For the present investigation, 44 germplasm samples were collected from Jinping County of Yunnan Province. Clusters analysis and 2-dimensional principal component analysis (PCA) was used to represent the genetic relations among Amomum tsao-ko by using simple sequence repeat (SSR) markers. Clustering analysis clearly distinguished the samples groups. Two major clusters were formed; first (Cluster I) consisted of 34 individuals, the second (Cluster II) consisted of 10 individuals, Cluster I as the main group contained multiple sub-clusters. PCA also showed 2 groups: PCA Group 1 included 29 individuals, PCA Group 2 included 12 individuals, consistent with the results of cluster analysis. The purpose of the present investigation was to provide information on genetic relationship of Amomum tsao-ko germplasm resources in main producing areas, also provide a theoretical basis for the protection and utilization of Amomum tsao-ko resources.

A new statistic for identifying batch effects in high-throughput genomic data that uses guided principal component analysis.

PubMed

Reese, Sarah E; Archer, Kellie J; Therneau, Terry M; Atkinson, Elizabeth J; Vachon, Celine M; de Andrade, Mariza; Kocher, Jean-Pierre A; Eckel-Passow, Jeanette E

2013-11-15

Batch effects are due to probe-specific systematic variation between groups of samples (batches) resulting from experimental features that are not of biological interest. Principal component analysis (PCA) is commonly used as a visual tool to determine whether batch effects exist after applying a global normalization method. However, PCA yields linear combinations of the variables that contribute maximum variance and thus will not necessarily detect batch effects if they are not the largest source of variability in the data. We present an extension of PCA to quantify the existence of batch effects, called guided PCA (gPCA). We describe a test statistic that uses gPCA to test whether a batch effect exists. We apply our proposed test statistic derived using gPCA to simulated data and to two copy number variation case studies: the first study consisted of 614 samples from a breast cancer family study using Illumina Human 660 bead-chip arrays, whereas the second case study consisted of 703 samples from a family blood pressure study that used Affymetrix SNP Array 6.0. We demonstrate that our statistic has good statistical properties and is able to identify significant batch effects in two copy number variation case studies. We developed a new statistic that uses gPCA to identify whether batch effects exist in high-throughput genomic data. Although our examples pertain to copy number data, gPCA is general and can be used on other data types as well. The gPCA R package (Available via CRAN) provides functionality and data to perform the methods in this article. reesese@vcu.edu

Application of principal component analysis for improvement of X-ray fluorescence images obtained by polycapillary-based micro-XRF technique

NASA Astrophysics Data System (ADS)

Aida, S.; Matsuno, T.; Hasegawa, T.; Tsuji, K.

2017-07-01

Micro X-ray fluorescence (micro-XRF) analysis is repeated as a means of producing elemental maps. In some cases, however, the XRF images of trace elements that are obtained are not clear due to high background intensity. To solve this problem, we applied principal component analysis (PCA) to XRF spectra. We focused on improving the quality of XRF images by applying PCA. XRF images of the dried residue of standard solution on the glass substrate were taken. The XRF intensities for the dried residue were analyzed before and after PCA. Standard deviations of XRF intensities in the PCA-filtered images were improved, leading to clear contrast of the images. This improvement of the XRF images was effective in cases where the XRF intensity was weak.

Contact- and distance-based principal component analysis of protein dynamics.

PubMed

Ernst, Matthias; Sittel, Florian; Stock, Gerhard

2015-12-28

To interpret molecular dynamics simulations of complex systems, systematic dimensionality reduction methods such as principal component analysis (PCA) represent a well-established and popular approach. Apart from Cartesian coordinates, internal coordinates, e.g., backbone dihedral angles or various kinds of distances, may be used as input data in a PCA. Adopting two well-known model problems, folding of villin headpiece and the functional dynamics of BPTI, a systematic study of PCA using distance-based measures is presented which employs distances between Cα-atoms as well as distances between inter-residue contacts including side chains. While this approach seems prohibitive for larger systems due to the quadratic scaling of the number of distances with the size of the molecule, it is shown that it is sufficient (and sometimes even better) to include only relatively few selected distances in the analysis. The quality of the PCA is assessed by considering the resolution of the resulting free energy landscape (to identify metastable conformational states and barriers) and the decay behavior of the corresponding autocorrelation functions (to test the time scale separation of the PCA). By comparing results obtained with distance-based, dihedral angle, and Cartesian coordinates, the study shows that the choice of input variables may drastically influence the outcome of a PCA.

Contact- and distance-based principal component analysis of protein dynamics

NASA Astrophysics Data System (ADS)

Ernst, Matthias; Sittel, Florian; Stock, Gerhard

2015-12-01

To interpret molecular dynamics simulations of complex systems, systematic dimensionality reduction methods such as principal component analysis (PCA) represent a well-established and popular approach. Apart from Cartesian coordinates, internal coordinates, e.g., backbone dihedral angles or various kinds of distances, may be used as input data in a PCA. Adopting two well-known model problems, folding of villin headpiece and the functional dynamics of BPTI, a systematic study of PCA using distance-based measures is presented which employs distances between Cα-atoms as well as distances between inter-residue contacts including side chains. While this approach seems prohibitive for larger systems due to the quadratic scaling of the number of distances with the size of the molecule, it is shown that it is sufficient (and sometimes even better) to include only relatively few selected distances in the analysis. The quality of the PCA is assessed by considering the resolution of the resulting free energy landscape (to identify metastable conformational states and barriers) and the decay behavior of the corresponding autocorrelation functions (to test the time scale separation of the PCA). By comparing results obtained with distance-based, dihedral angle, and Cartesian coordinates, the study shows that the choice of input variables may drastically influence the outcome of a PCA.

Urinary microRNAs for prostate cancer diagnosis, prognosis, and treatment response: are we there yet?

PubMed

Balacescu, Ovidiu; Petrut, Bogdan; Tudoran, Oana; Feflea, Dragos; Balacescu, Loredana; Anghel, Andrei; Sirbu, Ioan O; Seclaman, Edward; Marian, Catalin

2017-11-01

Prostate cancer (PCa) remains one of the leading causes of cancer-related deaths in men. Despite the tremendous progress in research over the years, a suitable minimally invasive PCa biomarker is yet to be discovered. The recent advances regarding the roles of microRNAs as biomarkers has allowed for their study in PCa as well, especially as blood-based markers. However, there are several studies that used urine as biological sample to evaluate microRNAs as biomarkers for PCa diagnosis, prognosis, and treatment response, which were reviewed herein. A high degree of inconsistency among reports has been observed, which could be due to several analytical aspects, starting with different urinary fractions used for analysis and continuing with the employment of various analytical platforms and methods of statistical analysis. However, a few microRNAs were found to be dysregulated in the urine of PCa patients, which alone or together with serum prostate-specific antigen seem to improve diagnostic power even in the gray zone of PCa. These results warrant further confirmation by larger prospective studies, preferably using a standardized protocol for analysis. WIREs RNA 2017, 8:e1438. doi: 10.1002/wrna.1438 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

Prostate Cancer Patients-Negative Biopsy Controls Discrimination by Untargeted Metabolomics Analysis of Urine by LC-QTOF: Upstream Information on Other Omics

NASA Astrophysics Data System (ADS)

Fernández-Peralbo, M. A.; Gómez-Gómez, E.; Calderón-Santiago, M.; Carrasco-Valiente, J.; Ruiz-García, J.; Requena-Tapia, M. J.; Luque de Castro, M. D.; Priego-Capote, F.

2016-12-01

The existing clinical biomarkers for prostate cancer (PCa) diagnosis are far from ideal (e.g., the prostate specific antigen (PSA) serum level suffers from lack of specificity, providing frequent false positives leading to over-diagnosis). A key step in the search for minimum invasive tests to complement or replace PSA should be supported on the changes experienced by the biochemical pathways in PCa patients as compared to negative biopsy control individuals. In this research a comprehensive global analysis by LC-QTOF was applied to urine from 62 patients with a clinically significant PCa and 42 healthy individuals, both groups confirmed by biopsy. An unpaired t-test (p-value < 0.05) provided 28 significant metabolites tentatively identified in urine, used to develop a partial least squares discriminant analysis (PLS-DA) model characterized by 88.4 and 92.9% of sensitivity and specificity, respectively. Among the 28 significant metabolites 27 were present at lower concentrations in PCa patients than in control individuals, while only one reported higher concentrations in PCa patients. The connection among the biochemical pathways in which they are involved (DNA methylation, epigenetic marks on histones and RNA cap methylation) could explain the concentration changes with PCa and supports, once again, the role of metabolomics in upstream processes.

Silibinin inhibits prostate cancer cells- and RANKL-induced osteoclastogenesis by targeting NFATc1, NF-κB, and AP-1 activation in RAW264.7 cells.

PubMed

Kavitha, Chandagirikoppal V; Deep, Gagan; Gangar, Subhash C; Jain, Anil K; Agarwal, Chapla; Agarwal, Rajesh

2014-03-01

Currently, there are limited therapeutic options against bone metastatic prostate cancer (PCA), which is primarily responsible for high mortality and morbidity in PCA patients. Enhanced osteoclastogenesis is an essential feature associated with metastatic PCA in the bone microenvironment. Silibinin, an effective chemopreventive agent, is in phase II clinical trials in PCA patients but its efficacy against PCA cells-induced osteoclastogenesis is largely unknown. Accordingly, here we examined silibinin effect on PCA cells-induced osteoclastogenesis employing human PCA (PC3MM2, PC3, and C4-2B) and murine macrophage RAW264.7 cells. We also assessed silibinin effect on receptor activator of nuclear factor κB ligand (RANKL)-induced signaling associated with osteoclast differentiation in RAW264.7 cells. Further, we analyzed silibinin effect on osteomimicry biomarkers in PCA cells. Results revealed that silibinin (30-90 μM) inhibits PCA cells-induced osteoclast activity and differentiation in RAW264.7 cells via modulating expression of several cytokines (IGF-1, TGF-β, TNF-α, I-TAC, M-CSF, G-CSF, GM-CSF, etc.) that are important in osteoclastogenesis. Additionally, in RAW264.7 cells, silibinin decreased the RANKL-induced expression and nuclear localization of NFATc1, which is considered the master regulator of osteoclastogenesis. Furthermore, silibinin decreased the RANKL-induced DNA binding activity of NFATc1 and its regulators NF-κB and AP1, and the protein expression of osteoclast specific markers (TRAP, OSCAR, and cathepsin K). Importantly, silibinin also decreased the expression of osteomimicry biomarkers (RANKL, Runx2, osteocalcin, and PTHrP) in cell culture (PC3 and C4-2B cells) and/or in PC3 tumors. Together, our findings showing that silibinin inhibits PCA cells-induced osteoclastogenesis, suggest that silibinin could be useful clinically against bone metastatic PCA. © 2013 Wiley Periodicals, Inc.

Has your ancient stamp been regummed with synthetic glue? A FT-NIR and FT-Raman study.

PubMed

Simonetti, Remo; Oliveri, Paolo; Henry, Adrien; Duponchel, Ludovic; Lanteri, Silvia

2016-01-01

The potential of FT-NIR and FT-Raman spectroscopies to characterise the gum applied on the backside of ancient stamps was investigated for the first time. This represents a very critical issue for the collectors' market, since gum conditions heavily influence stamp quotations, and fraudulent application of synthetic gum onto damaged stamp backsides to increase their desirability is a well-documented practice. Spectral data were processed by exploratory pattern recognition tools. In particular, application of principal component analysis (PCA) revealed that both of the spectroscopic techniques provide information useful to characterise stamp gum. Examination of PCA loadings and their chemical interpretation confirmed the robustness of the outcomes. Fusion of FT-NIR and FT-Raman spectral data was performed, following both a low-level and a mid-level procedure. The results were critically compared with those obtained separately for the two spectroscopic techniques. Copyright © 2015 Elsevier B.V. All rights reserved.

Inflammation: an important parameter in the search of prostate cancer biomarkers

PubMed Central

2014-01-01

Background A more specific and early diagnostics for prostate cancer (PCa) is highly desirable. In this study, being inflammation the focus of our effort, serum protein profiles were analyzed in order to investigate if this parameter could interfere with the search of discriminating proteins between PCa and benign prostatic hyperplasia (BPH). Methods Patients with clinical suspect of PCa and candidates for trans-rectal ultrasound guided prostate biopsy (TRUS) were enrolled. Histological specimens were examined in order to grade and classify the tumor, identify BPH and detect inflammation. Surface Enhanced Laser Desorption/Ionization-Time of Flight-Mass Spectrometry (SELDI-ToF-MS) and two-dimensional gel electrophoresis (2-DE) coupled with Liquid Chromatography-MS/MS (LC-MS/MS) were used to analyze immuno-depleted serum samples from patients with PCa and BPH. Results The comparison between PCa (with and without inflammation) and BPH (with and without inflammation) serum samples by SELDI-ToF-MS analysis did not show differences in protein expression, while changes were only observed when the concomitant presence of inflammation was taken into consideration. In fact, when samples with histological sign of inflammation were excluded, 20 significantly different protein peaks were detected. Subsequent comparisons (PCa with inflammation vs PCa without inflammation, and BPH with inflammation vs BPH without inflammation) showed that 16 proteins appeared to be modified in the presence of inflammation, while 4 protein peaks were not modified. With 2-DE analysis, comparing PCa without inflammation vs PCa with inflammation, and BPH without inflammation vs the same condition in the presence of inflammation, were identified 29 and 25 differentially expressed protein spots, respectively. Excluding samples with inflammation the comparison between PCa vs BPH showed 9 unique PCa proteins, 4 of which overlapped with those previously identified in the presence of inflammation, while other 2 were new proteins, not identified in our previous comparisons. Conclusions The present study indicates that inflammation might be a confounding parameter during the proteomic research of candidate biomarkers of PCa. These results indicate that some possible biomarker-candidate proteins are strongly influenced by the presence of inflammation, hence only a well-selected protein pattern should be considered for potential marker of PCa. PMID:24944525

Can Prostate Imaging Reporting and Data System Version 2 reduce unnecessary prostate biopsies in men with PSA levels of 4-10 ng/ml?

PubMed

Xu, Ning; Wu, Yu-Peng; Chen, Dong-Ning; Ke, Zhi-Bin; Cai, Hai; Wei, Yong; Zheng, Qing-Shui; Huang, Jin-Bei; Li, Xiao-Dong; Xue, Xue-Yi

2018-05-01

To explore the value of Prostate Imaging Reporting and Data System Version 2 (PI-RADS v2) for predicting prostate biopsy results in patients with prostate specific antigen (PSA) levels of 4-10 ng/ml. We retrospectively reviewed multi-parameter magnetic resonance images from 528 patients with PSA levels of 4-10 ng/ml who underwent transrectal ultrasound-guided prostate biopsies between May 2015 and May 2017. Among them, 137 were diagnosed with prostate cancer (PCa), and we further subdivided them according to pathological results into the significant PCa (S-PCa) and insignificant significant PCa (Ins-PCa) groups (121 cases were defined by surgical pathological specimen and 16 by biopsy). Age, PSA, percent free PSA, PSA density (PSAD), prostate volume (PV), and PI-RADS score were collected. Logistic regression analysis was performed to determine predictors of pathological results. Receiver operating characteristic curves were constructed to analyze the diagnostic value of PI-RADS v2 in PCa. Multivariate analysis indicated that age, PV, percent free PSA, and PI-RADS score were independent predictors of biopsy findings, while only PI-RADS score was an independent predictor of S-PCa (P < 0.05). The areas under the receiver operating characteristic curve for diagnosing PCa with respect to age, PV, percent free PSA, and PI-RADS score were 0.570, 0.430, 0.589 and 0.836, respectively. The area under the curve for diagnosing S-PCa with respect to PI-RADS score was 0.732. A PI-RADS score of 3 was the best cutoff for predicting PCa, and 4 was the best cutoff for predicting S-PCa. Thus, 92.8% of patients with PI-RADS scores of 1-2 would have avoided biopsy, but at the cost of missing 2.2% of the potential PCa cases. Similarly, 83.82% of patients with a PI-RADS score ≤ 3 would have avoided biopsy, but at the cost of missing 3.3% of the potential S-PCa cases. PI-RADS v2 could be used to reduce unnecessary prostate biopsies in patients with PSA levels of 4-10 ng/ml.

The histogram analysis of diffusion-weighted intravoxel incoherent motion (IVIM) imaging for differentiating the gleason grade of prostate cancer.

PubMed

Zhang, Yu-Dong; Wang, Qing; Wu, Chen-Jiang; Wang, Xiao-Ning; Zhang, Jing; Liu, Hui; Liu, Xi-Sheng; Shi, Hai-Bin

2015-04-01

To evaluate histogram analysis of intravoxel incoherent motion (IVIM) for discriminating the Gleason grade of prostate cancer (PCa). A total of 48 patients pathologically confirmed as having clinically significant PCa (size > 0.5 cm) underwent preoperative DW-MRI (b of 0-900 s/mm(2)). Data was post-processed by monoexponential and IVIM model for quantitation of apparent diffusion coefficients (ADCs), perfusion fraction f, diffusivity D and pseudo-diffusivity D*. Histogram analysis was performed by outlining entire-tumour regions of interest (ROIs) from histological-radiological correlation. The ability of imaging indices to differentiate low-grade (LG, Gleason score (GS) ≤6) from intermediate/high-grade (HG, GS > 6) PCa was analysed by ROC regression. Eleven patients had LG tumours (18 foci) and 37 patients had HG tumours (42 foci) on pathology examination. HG tumours had significantly lower ADCs and D in terms of mean, median, 10th and 75th percentiles, combined with higher histogram kurtosis and skewness for ADCs, D and f, than LG PCa (p < 0.05). Histogram D showed relatively higher correlations (ñ = 0.641-0.668 vs. ADCs: 0.544-0.574) with ordinal GS of PCa; and its mean, median and 10th percentile performed better than ADCs did in distinguishing LG from HG PCa. It is feasible to stratify the pathological grade of PCa by IVIM with histogram metrics. D performed better in distinguishing LG from HG tumour than conventional ADCs. • GS had relatively higher correlation with tumour D than ADCs. • Difference of histogram D among two-grade tumours was statistically significant. • D yielded better individual features in demonstrating tumour grade than ADC. • D* and f failed to determine tumour grade of PCa.

Detecting most influencing courses on students grades using block PCA

NASA Astrophysics Data System (ADS)

Othman, Osama H.; Gebril, Rami Salah

2014-12-01

One of the modern solutions adopted in dealing with the problem of large number of variables in statistical analyses is the Block Principal Component Analysis (Block PCA). This modified technique can be used to reduce the vertical dimension (variables) of the data matrix Xn×p by selecting a smaller number of variables, (say m) containing most of the statistical information. These selected variables can then be employed in further investigations and analyses. Block PCA is an adapted multistage technique of the original PCA. It involves the application of Cluster Analysis (CA) and variable selection throughout sub principal components scores (PC's). The application of Block PCA in this paper is a modified version of the original work of Liu et al (2002). The main objective was to apply PCA on each group of variables, (established using cluster analysis), instead of involving the whole large pack of variables which was proved to be unreliable. In this work, the Block PCA is used to reduce the size of a huge data matrix ((n = 41) × (p = 251)) consisting of Grade Point Average (GPA) of the students in 251 courses (variables) in the faculty of science in Benghazi University. In other words, we are constructing a smaller analytical data matrix of the GPA's of the students with less variables containing most variation (statistical information) in the original database. By applying the Block PCA, (12) courses were found to `absorb' most of the variation or influence from the original data matrix, and hence worth to be keep for future statistical exploring and analytical studies. In addition, the course Independent Study (Math.) was found to be the most influencing course on students GPA among the 12 selected courses.

Spectral discrimination of serum from liver cancer and liver cirrhosis using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Yang, Tianyue; Li, Xiaozhou; Yu, Ting; Sun, Ruomin; Li, Siqi

2011-07-01

In this paper, Raman spectra of human serum were measured using Raman spectroscopy, then the spectra was analyzed by multivariate statistical methods of principal component analysis (PCA). Then linear discriminant analysis (LDA) was utilized to differentiate the loading score of different diseases as the diagnosing algorithm. Artificial neural network (ANN) was used for cross-validation. The diagnosis sensitivity and specificity by PCA-LDA are 88% and 79%, while that of the PCA-ANN are 89% and 95%. It can be seen that modern analyzing method is a useful tool for the analysis of serum spectra for diagnosing diseases.

Investigation of domain walls in PPLN by confocal raman microscopy and PCA analysis

NASA Astrophysics Data System (ADS)

Shur, Vladimir Ya.; Zelenovskiy, Pavel; Bourson, Patrice

2017-07-01

Confocal Raman microscopy (CRM) is a powerful tool for investigation of ferroelectric domains. Mechanical stresses and electric fields existed in the vicinity of neutral and charged domain walls modify frequency, intensity and width of spectral lines [1], thus allowing to visualize micro- and nanodomain structures both at the surface and in the bulk of the crystal [2,3]. Stresses and fields are naturally coupled in ferroelectrics due to inverse piezoelectric effect and hardly can be separated in Raman spectra. PCA is a powerful statistical method for analysis of large data matrix providing a set of orthogonal variables, called principal components (PCs). PCA is widely used for classification of experimental data, for example, in crystallization experiments, for detection of small amounts of components in solid mixtures etc. [4,5]. In Raman spectroscopy PCA was applied for analysis of phase transitions and provided critical pressure with good accuracy [6]. In the present work we for the first time applied Principal Component Analysis (PCA) method for analysis of Raman spectra measured in periodically poled lithium niobate (PPLN). We found that principal components demonstrate different sensitivity to mechanical stresses and electric fields in the vicinity of the domain walls. This allowed us to separately visualize spatial distribution of fields and electric fields at the surface and in the bulk of PPLN.

Subject order-independent group ICA (SOI-GICA) for functional MRI data analysis.

PubMed

Zhang, Han; Zuo, Xi-Nian; Ma, Shuang-Ye; Zang, Yu-Feng; Milham, Michael P; Zhu, Chao-Zhe

2010-07-15

Independent component analysis (ICA) is a data-driven approach to study functional magnetic resonance imaging (fMRI) data. Particularly, for group analysis on multiple subjects, temporally concatenation group ICA (TC-GICA) is intensively used. However, due to the usually limited computational capability, data reduction with principal component analysis (PCA: a standard preprocessing step of ICA decomposition) is difficult to achieve for a large dataset. To overcome this, TC-GICA employs multiple-stage PCA data reduction. Such multiple-stage PCA data reduction, however, leads to variable outputs due to different subject concatenation orders. Consequently, the ICA algorithm uses the variable multiple-stage PCA outputs and generates variable decompositions. In this study, a rigorous theoretical analysis was conducted to prove the existence of such variability. Simulated and real fMRI experiments were used to demonstrate the subject-order-induced variability of TC-GICA results using multiple PCA data reductions. To solve this problem, we propose a new subject order-independent group ICA (SOI-GICA). Both simulated and real fMRI data experiments demonstrated the high robustness and accuracy of the SOI-GICA results compared to those of traditional TC-GICA. Accordingly, we recommend SOI-GICA for group ICA-based fMRI studies, especially those with large data sets. Copyright 2010 Elsevier Inc. All rights reserved.

PBOV1 as a potential biomarker for more advanced prostate cancer based on protein and digital histomorphometric analysis.

PubMed

Carleton, Neil M; Zhu, Guangjing; Gorbounov, Mikhail; Miller, M Craig; Pienta, Kenneth J; Resar, Linda M S; Veltri, Robert W

2018-05-01

There are few tissue-based biomarkers that can accurately predict prostate cancer (PCa) progression and aggressiveness. We sought to evaluate the clinical utility of prostate and breast overexpressed 1 (PBOV1) as a potential PCa biomarker. Patient tumor samples were designated by Grade Groups using the 2014 Gleason grading system. Primary radical prostatectomy tumors were obtained from 48 patients and evaluated for PBOV1 levels using Western blot analysis in matched cancer and benign cancer-adjacent regions. Immunohistochemical evaluation of PBOV1 was subsequently performed in 80 cancer and 80 benign cancer-adjacent patient samples across two tissue microarrays (TMAs) to verify protein levels in epithelial tissue and to assess correlation between PBOV1 proteins and nuclear architectural changes in PCa cells. Digital histomorphometric analysis was used to track 22 parameters that characterized nuclear changes in PBOV1-stained cells. Using a training and test set for validation, multivariate logistic regression (MLR) models were used to identify significant nuclear parameters that distinguish Grade Group 3 and above PCa from Grade Group 1 and 2 PCa regions. PBOV1 protein levels were increased in tumors from Grade Group 3 and above (GS 4 + 3 and ≥ 8) regions versus Grade Groups 1 and 2 (GS 3 + 3 and 3 + 4) regions (P = 0.005) as assessed by densitometry of immunoblots. Additionally, by immunoblotting, PBOV1 protein levels differed significantly between Grade Group 2 (GS 3 + 4) and Grade Group 3 (GS 4 + 3) PCa samples (P = 0.028). In the immunohistochemical analysis, measures of PBOV1 staining intensity strongly correlated with nuclear alterations in cancer cells. An MLR model retaining eight parameters describing PBOV1 staining intensity and nuclear architecture discriminated Grade Group 3 and above PCa from Grade Group 1 and 2 PCa and benign cancer-adjacent regions with a ROC-AUC of 0.90 and 0.80, respectively, in training and test sets. Our study demonstrates that the PBOV1 protein could be used to discriminate Grade Group 3 and above PCa. Additionally, the PBOV1 protein could be involved in modulating changes to the nuclear architecture of PCa cells. Confirmatory studies are warranted in an independent population for further validation. © 2018 Wiley Periodicals, Inc.

Conformational flexibility of the ErbB2 ectodomain and trastuzumab antibody complex as revealed by molecular dynamics and principal component analysis.

PubMed

Franco-Gonzalez, Juan Felipe; Cruz, Victor L; Ramos, Javier; Martínez-Salazar, Javier

2013-03-01

Human epidermal growth factor receptor 2 (ErbB2) is a transmembrane oncoprotein that is over expressed in breast cancer. A successful therapeutic treatment is a monoclonal antibody called trastuzumab which interacts with the ErbB2 extracellular domain (ErbB2-ECD). A better understanding of the detailed structure of the receptor-antibody interaction is indeed of prime interest for the design of more effective anticancer therapies. In order to discuss the flexibility of the complex ErbB2-ECD/trastuzumab, we present, in this study, a multi-nanosecond molecular dynamics simulation (MD) together with an analysis of fluctuations, through a principal component analysis (PCA) of this system. Previous to this step and in order to validate the simulations, we have performed a detailed analysis of the variable antibody domain interactions with the extracellular domain IV of ErbB2. This structure has been statically elucidated by x-ray studies. Indeed, the simulation results are in excellent agreement with the available experimental information during the full trajectory. The PCA shows eigenvector fluctuations resulting in a hinge motion in which domain II and C(H) domains approach each other. This move is likely stabilized by the formation of H-bonds and salt bridge interactions between residues of the dimerization arm in the domain II and trastuzumab residues located in the C(H) domain. Finally, we discuss the flexibility of the MD/PCA model in relation with the static x-ray structure. A movement of the antibody toward the dimerization domain of the ErbB2 receptor is reported for the first time. This finding could have important consequences on the biological action of the monoclonal antibody.

Genome-Wide Divergence and Linkage Disequilibrium Analyses for Capsicum baccatum Revealed by Genome-Anchored Single Nucleotide Polymorphisms

PubMed Central

Nimmakayala, Padma; Abburi, Venkata L.; Saminathan, Thangasamy; Almeida, Aldo; Davenport, Brittany; Davidson, Joshua; Reddy, C. V. Chandra Mohan; Hankins, Gerald; Ebert, Andreas; Choi, Doil; Stommel, John; Reddy, Umesh K.

2016-01-01

Principal component analysis (PCA) with 36,621 polymorphic genome-anchored single nucleotide polymorphisms (SNPs) identified collectively for Capsicum annuum and Capsicum baccatum was used to characterize population structure and species domestication of these two important incompatible cultivated pepper species. Estimated mean nucleotide diversity (π) and Tajima's D across various chromosomes revealed biased distribution toward negative values on all chromosomes (except for chromosome 4) in cultivated C. baccatum, indicating a population bottleneck during domestication of C. baccatum. In contrast, C. annuum chromosomes showed positive π and Tajima's D on all chromosomes except chromosome 8, which may be because of domestication at multiple sites contributing to wider genetic diversity. For C. baccatum, 13,129 SNPs were available, with minor allele frequency (MAF) ≥0.05; PCA of the SNPs revealed 283 C. baccatum accessions grouped into 3 distinct clusters, for strong population structure. The fixation index (FST) between domesticated C. annuum and C. baccatum was 0.78, which indicates genome-wide divergence. We conducted extensive linkage disequilibrium (LD) analysis of C. baccatum var. pendulum cultivars on all adjacent SNP pairs within a chromosome to identify regions of high and low LD interspersed with a genome-wide average LD block size of 99.1 kb. We characterized 1742 haplotypes containing 4420 SNPs (range 9–2 SNPs per haplotype). Genome-wide association study (GWAS) of peduncle length, a trait that differentiates wild and domesticated C. baccatum types, revealed 36 significantly associated genome-wide SNPs. Population structure, identity by state (IBS) and LD patterns across the genome will be of potential use for future GWAS of economically important traits in C. baccatum peppers. PMID:27857720

Genome-Wide Divergence and Linkage Disequilibrium Analyses for Capsicum baccatum Revealed by Genome-Anchored Single Nucleotide Polymorphisms.

PubMed

Nimmakayala, Padma; Abburi, Venkata L; Saminathan, Thangasamy; Almeida, Aldo; Davenport, Brittany; Davidson, Joshua; Reddy, C V Chandra Mohan; Hankins, Gerald; Ebert, Andreas; Choi, Doil; Stommel, John; Reddy, Umesh K

2016-01-01

Principal component analysis (PCA) with 36,621 polymorphic genome-anchored single nucleotide polymorphisms (SNPs) identified collectively for Capsicum annuum and Capsicum baccatum was used to characterize population structure and species domestication of these two important incompatible cultivated pepper species. Estimated mean nucleotide diversity (π) and Tajima's D across various chromosomes revealed biased distribution toward negative values on all chromosomes (except for chromosome 4) in cultivated C. baccatum , indicating a population bottleneck during domestication of C. baccatum . In contrast, C. annuum chromosomes showed positive π and Tajima's D on all chromosomes except chromosome 8, which may be because of domestication at multiple sites contributing to wider genetic diversity. For C. baccatum , 13,129 SNPs were available, with minor allele frequency (MAF) ≥0.05; PCA of the SNPs revealed 283 C. baccatum accessions grouped into 3 distinct clusters, for strong population structure. The fixation index ( F ST ) between domesticated C. annuum and C. baccatum was 0.78, which indicates genome-wide divergence. We conducted extensive linkage disequilibrium (LD) analysis of C. baccatum var. pendulum cultivars on all adjacent SNP pairs within a chromosome to identify regions of high and low LD interspersed with a genome-wide average LD block size of 99.1 kb. We characterized 1742 haplotypes containing 4420 SNPs (range 9-2 SNPs per haplotype). Genome-wide association study (GWAS) of peduncle length, a trait that differentiates wild and domesticated C. baccatum types, revealed 36 significantly associated genome-wide SNPs. Population structure, identity by state (IBS) and LD patterns across the genome will be of potential use for future GWAS of economically important traits in C. baccatum peppers.

Principal component analysis for the comparison of metabolic profiles from human rectal cancer biopsies and colorectal xenografts using high-resolution magic angle spinning 1H magnetic resonance spectroscopy

PubMed Central

Seierstad, Therese; Røe, Kathrine; Sitter, Beathe; Halgunset, Jostein; Flatmark, Kjersti; Ree, Anne H; Olsen, Dag Rune; Gribbestad, Ingrid S; Bathen, Tone F

2008-01-01

Background This study was conducted in order to elucidate metabolic differences between human rectal cancer biopsies and colorectal HT29, HCT116 and SW620 xenografts by using high-resolution magnetic angle spinning (MAS) magnetic resonance spectroscopy (MRS) and for determination of the most appropriate human rectal xenograft model for preclinical MR spectroscopy studies. A further aim was to investigate metabolic changes following irradiation of HT29 xenografts. Methods HR MAS MRS of tissue samples from xenografts and rectal biopsies were obtained with a Bruker Avance DRX600 spectrometer and analyzed using principal component analysis (PCA) and partial least square (PLS) regression analysis. Results and conclusion HR MAS MRS enabled assignment of 27 metabolites. Score plots from PCA of spin-echo and single-pulse spectra revealed separate clusters of the different xenografts and rectal biopsies, reflecting underlying differences in metabolite composition. The loading profile indicated that clustering was mainly based on differences in relative amounts of lipids, lactate and choline-containing compounds, with HT29 exhibiting the metabolic profile most similar to human rectal cancers tissue. Due to high necrotic fractions in the HT29 xenografts, radiation-induced changes were not detected when comparing spectra from untreated and irradiated HT29 xenografts. However, PLS calibration relating spectral data to the necrotic fraction revealed a significant correlation, indicating that necrotic fraction can be assessed from the MR spectra. PMID:18439252

On application of kernel PCA for generating stimulus features for fMRI during continuous music listening.

PubMed

Tsatsishvili, Valeri; Burunat, Iballa; Cong, Fengyu; Toiviainen, Petri; Alluri, Vinoo; Ristaniemi, Tapani

2018-06-01

There has been growing interest towards naturalistic neuroimaging experiments, which deepen our understanding of how human brain processes and integrates incoming streams of multifaceted sensory information, as commonly occurs in real world. Music is a good example of such complex continuous phenomenon. In a few recent fMRI studies examining neural correlates of music in continuous listening settings, multiple perceptual attributes of music stimulus were represented by a set of high-level features, produced as the linear combination of the acoustic descriptors computationally extracted from the stimulus audio. NEW METHOD: fMRI data from naturalistic music listening experiment were employed here. Kernel principal component analysis (KPCA) was applied to acoustic descriptors extracted from the stimulus audio to generate a set of nonlinear stimulus features. Subsequently, perceptual and neural correlates of the generated high-level features were examined. The generated features captured musical percepts that were hidden from the linear PCA features, namely Rhythmic Complexity and Event Synchronicity. Neural correlates of the new features revealed activations associated to processing of complex rhythms, including auditory, motor, and frontal areas. Results were compared with the findings in the previously published study, which analyzed the same fMRI data but applied linear PCA for generating stimulus features. To enable comparison of the results, methodology for finding stimulus-driven functional maps was adopted from the previous study. Exploiting nonlinear relationships among acoustic descriptors can lead to the novel high-level stimulus features, which can in turn reveal new brain structures involved in music processing. Copyright © 2018 Elsevier B.V. All rights reserved.

Physicochemical and mechanical properties of paracetamol cocrystal with 5-nitroisophthalic acid.

PubMed

Hiendrawan, Stevanus; Veriansyah, Bambang; Widjojokusumo, Edward; Soewandhi, Sundani Nurono; Wikarsa, Saleh; Tjandrawinata, Raymond R

2016-01-30

We report novel pharmaceutical cocrystal of a popular antipyretic drug paracetamol (PCA) with coformer 5-nitroisophhthalic acid (5NIP) to improve its tabletability. The cocrystal (PCA-5NIP at molar ratio of 1:1) was synthesized by solvent evaporation technique using methanol as solvent. The physicochemical properties of cocrystal were characterized by powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), thermogravimetry analysis (TGA), fourier transform infrared spectroscopy (FTIR), hot stage polarized microscopy (HSPM) and scanning electron microscopy (SEM). Stability of the cocrystal was assessed by storing them at 40°C/75% RH for one month. Compared to PCA, the cocrystal displayed superior tableting performance. PCA-5NIP cocrystal showed a similar dissolution profile as compared to PCA and exhibited good stability. This study showed the utility of PCA-5NIP cocrystal for improving mechanical properties of PCA. Copyright © 2015 Elsevier B.V. All rights reserved.

PEM-PCA: a parallel expectation-maximization PCA face recognition architecture.

PubMed

Rujirakul, Kanokmon; So-In, Chakchai; Arnonkijpanich, Banchar

2014-01-01

Principal component analysis or PCA has been traditionally used as one of the feature extraction techniques in face recognition systems yielding high accuracy when requiring a small number of features. However, the covariance matrix and eigenvalue decomposition stages cause high computational complexity, especially for a large database. Thus, this research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages' complexity. To improve the computational time, a novel parallel architecture was employed to utilize the benefits of parallelization of matrix computation during feature extraction and classification stages including parallel preprocessing, and their combinations, so-called a Parallel Expectation-Maximization PCA architecture. Comparing to a traditional PCA and its derivatives, the results indicate lower complexity with an insignificant difference in recognition precision leading to high speed face recognition systems, that is, the speed-up over nine and three times over PCA and Parallel PCA.

A cadmium-transporting P1B-type ATPase in yeast Saccharomyces cerevisiae.

PubMed

Adle, David J; Sinani, Devis; Kim, Heejeong; Lee, Jaekwon

2007-01-12

Detoxification and homeostatic acquisition of metal ions are vital for all living organisms. We have identified PCA1 in yeast Saccharomyces cerevisiae as an overexpression suppressor of copper toxicity. PCA1 possesses signatures of a P1B-type heavy metal-transporting ATPase that is widely distributed from bacteria to humans. Copper resistance conferred by PCA1 is not dependent on catalytic activity, but it appears that a cysteine-rich region located in the N terminus sequesters copper. Unexpectedly, when compared with two independent natural isolates and an industrial S. cerevisiae strain, the PCA1 allele of the common laboratory strains we have examined possesses a missense mutation in a predicted ATP-binding residue conserved in P1B-type ATPases. Consistent with a previous report that identifies an equivalent mutation in a copper-transporting P1B-type ATPase of a Wilson disease patient, the PCA1 allele found in laboratory yeast strains is nonfunctional. Overexpression or deletion of the functional allele in yeast demonstrates that PCA1 is a cadmium efflux pump. Cadmium as well as copper and silver, but not other metals examined, dramatically increase PCA1 protein expression through post-transcriptional regulation and promote subcellular localization to the plasma membrane. Our study has revealed a novel metal detoxification mechanism in yeast mediated by a P1B-type ATPase that is unique in structure, substrate specificity, and mode of regulation.

Revealing the properties of oils from their dissolved hydrocarbon compounds in water with an integrated sensor array system.

PubMed

Qi, Xiubin; Crooke, Emma; Ross, Andrew; Bastow, Trevor P; Stalvies, Charlotte

2011-09-21

This paper presents a system and method developed to identify a source oil's characteristic properties by testing the oil's dissolved components in water. Through close examination of the oil dissolution process in water, we hypothesise that when oil is in contact with water, the resulting oil-water extract, a complex hydrocarbon mixture, carries the signature property information of the parent oil. If the dominating differences in compositions between such extracts of different oils can be identified, this information could guide the selection of various sensors, capable of capturing such chemical variations. When used as an array, such a sensor system can be used to determine parent oil information from the oil-water extract. To test this hypothesis, 22 oils' water extracts were prepared and selected dominant hydrocarbons analyzed with Gas Chromatography-Mass Spectrometry (GC-MS); the subsequent Principal Component Analysis (PCA) indicates that the major difference between the extract solutions is the relative concentration between the volatile mono-aromatics and fluorescent polyaromatics. An integrated sensor array system that is composed of 3 volatile hydrocarbon sensors and 2 polyaromatic hydrocarbon sensors was built accordingly to capture the major and subtle differences of these extracts. It was tested by exposure to a total of 110 water extract solutions diluted from the 22 extracts. The sensor response data collected from the testing were processed with two multivariate analysis tools to reveal information retained in the response patterns of the arrayed sensors: by conducting PCA, we were able to demonstrate the ability to qualitatively identify and distinguish different oil samples from their sensor array response patterns. When a supervised PCA, Linear Discriminate Analysis (LDA), was applied, even quantitative classification can be achieved: the multivariate model generated from the LDA achieved 89.7% of successful classification of the type of the oil samples. By grouping the samples based on the level of viscosity and density we were able to reveal the correlation between the oil extracts' sensor array responses and their original oils' feature properties. The equipment and method developed in this study have promising potential to be readily applied in field studies and marine surveys for oil exploration or oil spill monitoring.

UPLC-QTOF analysis reveals metabolomic changes in the flag leaf of wheat (Triticum aestivum L.) under low-nitrogen stress.

PubMed

Zhang, Yang; Ma, Xin-Ming; Wang, Xiao-Chun; Liu, Ji-Hong; Huang, Bing-Yan; Guo, Xiao-Yang; Xiong, Shu-Ping; La, Gui-Xiao

2017-02-01

Wheat is one of the most important grain crop plants worldwide. Nitrogen (N) is an essential macronutrient for the growth and development of wheat and exerts a marked influence on its metabolites. To investigate the influence of low nitrogen stress on various metabolites of the flag leaf of wheat (Triticum aestivum L.), a metabolomic analysis of two wheat cultivars under different induced nitrogen levels was conducted during two important growth periods based on large-scale untargeted metabolomic analysis using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF). Multivariate analyses-such as principle components analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA)-were used for data analysis. PCA yielded distinctive clustering information among the samples, classifying the wheat flag samples into two categories: those under normal N treatment and low N treatment. By processing OPLS-DA, eleven secondary metabolites were shown to be responsible for classifying the two groups. The secondary metabolites may be considered potential biomarkers of low nitrogen stress. Chemical analyses showed that most of the identified secondary metabolites were flavonoids and their related derivatives, such as iso-vitexin, iso-orientin and methylisoorientin-2″-O-rhamnoside, etc. This study confirmed the effect of low nitrogen stress on the metabolism of wheat, and revealed that the accumulation of secondary metabolites is a response to abiotic stresses. Meanwhile, we aimed to identify markers which could be used to monitor the nitrogen status of wheat crops, presumably to guide appropriate fertilization regimens. Furthermore, the UPLC-QTOF metabolic platform technology can be used to study metabolomic variations of wheat under abiotic stresses. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

RECENT APPLICATIONS OF SOURCE APPORTIONMENT METHODS AND RELATED NEEDS

EPA Science Inventory

Traditional receptor modeling studies have utilized factor analysis (like principal component analysis, PCA) and/or Chemical Mass Balance (CMB) to assess source influences. The limitations with these approaches is that PCA is qualitative and CMB requires the input of source pr...

Kernel Principal Component Analysis for dimensionality reduction in fMRI-based diagnosis of ADHD.

PubMed

Sidhu, Gagan S; Asgarian, Nasimeh; Greiner, Russell; Brown, Matthew R G

2012-01-01

This study explored various feature extraction methods for use in automated diagnosis of Attention-Deficit Hyperactivity Disorder (ADHD) from functional Magnetic Resonance Image (fMRI) data. Each participant's data consisted of a resting state fMRI scan as well as phenotypic data (age, gender, handedness, IQ, and site of scanning) from the ADHD-200 dataset. We used machine learning techniques to produce support vector machine (SVM) classifiers that attempted to differentiate between (1) all ADHD patients vs. healthy controls and (2) ADHD combined (ADHD-c) type vs. ADHD inattentive (ADHD-i) type vs. controls. In different tests, we used only the phenotypic data, only the imaging data, or else both the phenotypic and imaging data. For feature extraction on fMRI data, we tested the Fast Fourier Transform (FFT), different variants of Principal Component Analysis (PCA), and combinations of FFT and PCA. PCA variants included PCA over time (PCA-t), PCA over space and time (PCA-st), and kernelized PCA (kPCA-st). Baseline chance accuracy was 64.2% produced by guessing healthy control (the majority class) for all participants. Using only phenotypic data produced 72.9% accuracy on two class diagnosis and 66.8% on three class diagnosis. Diagnosis using only imaging data did not perform as well as phenotypic-only approaches. Using both phenotypic and imaging data with combined FFT and kPCA-st feature extraction yielded accuracies of 76.0% on two class diagnosis and 68.6% on three class diagnosis-better than phenotypic-only approaches. Our results demonstrate the potential of using FFT and kPCA-st with resting-state fMRI data as well as phenotypic data for automated diagnosis of ADHD. These results are encouraging given known challenges of learning ADHD diagnostic classifiers using the ADHD-200 dataset (see Brown et al., 2012).

Using the prostate imaging reporting and data system version 2 (PI-RIDS v2) to detect prostate cancer can prevent unnecessary biopsies and invasive treatment.

PubMed

Liu, Chang; Liu, Shi-Liang; Wang, Zhi-Xian; Yu, Kai; Feng, Chun-Xiang; Ke, Zan; Wang, Liang; Zeng, Xiao-Yong

2018-04-13

Prostate cancer (PCa) is one of the most common cancers among men globally. The authors aimed to evaluate the ability of the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) to classify men with PCa, clinically significant PCa (CSPCa), or no PCa, especially among those with serum total prostate-specific antigen (tPSA) levels in the "gray zone" (4-10 ng ml -1 ). A total of 308 patients (355 lesions) were enrolled in this study. Diagnostic efficiency was determined. Univariate and multivariate analyses, receiver operating characteristic curve analysis, and decision curve analysis were performed to determine and compare the predictors of PCa and CSPCa. The results suggested that PI-RADS v2, tPSA, and prostate-specific antigen density (PSAD) were independent predictors of PCa and CSPCa. A PI-RADS v2 score ≥4 provided high negative predictive values (91.39% for PCa and 95.69% for CSPCa). A model of PI-RADS combined with PSA and PSAD helped to define a high-risk group (PI-RADS score = 5 and PSAD ≥0.15 ng ml -1 cm -3 , with tPSA in the gray zone, or PI-RADS score ≥4 with high tPSA level) with a detection rate of 96.1% for PCa and 93.0% for CSPCa while a low-risk group with a detection rate of 6.1% for PCa and 2.2% for CSPCa. It was concluded that the PI-RADS v2 could be used as a reliable and independent predictor of PCa and CSPCa. The combination of PI-RADS v2 score with PSA and PSAD could be helpful in the prediction and diagnosis of PCa and CSPCa and, thus, may help in preventing unnecessary invasive procedures.

Prognostic Value of Neutrophil-to-Lymphocyte Ratio in Localized and Advanced Prostate Cancer: A Systematic Review and Meta-Analysis.

PubMed

Tang, Lu; Li, Xintao; Wang, Baojun; Luo, Guoxiong; Gu, Liangyou; Chen, Luyao; Liu, Kan; Gao, Yu; Zhang, Xu

2016-01-01

Increasing evidence suggests that inflammation plays an essential role in cancer development and progression. The inflammation marker neutrophil-lymphocyte ratio (NLR) is correlated with prognosis across a wide variety of tumor types, but its prognostic value in prostate cancer (PCa) remains controversial. In the present meta-analysis, the prognostic value of NLR in PCa patients is investigated. We performed a meta-analysis to determine the predictive value of NLR for overall survival (OS), recurrence-free survival (RFS), and clinical features in patients with PCa. We systematically searched PubMed, ISI Web of Science, and Embase for relevant studies published up to October 2015. A total of 9418 patients from 18 studies were included in the meta-analysis. Elevated pretreatment NLR predicted poor OS (HR 1.628, 95% CI 1.410-1.879) and RFS (HR 1.357, 95% CI 1.126-1.636) in all patients with PCa. However, NLR was insignificantly associated with OS in the subgroup of patients with localized PCa (HR 1.439, 95% CI 0.753-2.75). Increased NLR was also significantly correlated with lymph node involvement (OR 1.616, 95% CI 1.167-2.239) but not with pathological stage (OR 0.827, 95% CI 0.637-1.074) or Gleason score (OR 0.761, 95% CI 0.555-1.044). The present meta-analysis indicated that NLR could predict the prognosis for patients with locally advanced or castration-resistant PCa. Patients with higher NLR are more likely to have poorer prognosis than those with lower NLR.

The Burden of Urinary Incontinence and Urinary Bother Among Elderly Prostate Cancer Survivors

PubMed Central

Kopp, Ryan P.; Marshall, Lynn M.; Wang, Patty Y.; Bauer, Douglas C.; Barrett-Connor, Elizabeth; Parsons, J. Kellogg

2014-01-01

Background Data describing urinary health in elderly, community-dwelling prostate cancer (PCa) survivors are limited. Objective To elucidate the prevalence of lower urinary tract symptoms, urinary bother, and incontinence in elderly PCa survivors compared with peers without PCa. Design, setting, and participants A cross-sectional analysis of 5990 participants in the Osteoporotic Fractures in Men Research Group, a cohort study of community-dwelling men ≥65 yr. Outcome measurements and statistical analysis We characterized urinary health using self-reported urinary incontinence and the American Urological Association Symptom Index (AUA-SI). We compared urinary health measures according to type of PCa treatment in men with PCa and men without PCa using multivariate log-binomial regression to generate prevalence ratios (PRs). Results and limitations At baseline, 706 men (12%) reported a history of PCa, with a median time since diagnosis of 6.3 yr. Of these men, 426 (60%) reported urinary incontinence. In adjusted analyses, observation (PR: 1.92; 95% confidence interval [CI], 1.15–3.21; p = 0.01), surgery (PR: 4.68; 95% CI, 4.11–5.32; p < 0.0001), radiation therapy (PR: 1.64; 95% CI, 1.20– 2.23; p = 0.002), and androgen-deprivation therapy (ADT) (PR: 2.01; 95% CI, 1.35–2.99; p = 0.0006) were each associated with daily incontinence. Daily incontinence risk increased with time since diagnosis independently of age. Observation (PR: 1.33; 95% CI, 1.00–1.78; p = 0.05), surgery (PR: 1.25; 95% CI, 1.10–1.42; p = 0.0008), and ADT (PR: 1.50; 95% CI, 1.26–1.79; p < 0.0001) were associated with increased AUA-SI bother scores. Cancer stage and use of adjuvant or salvage therapies were not available for analysis. Conclusions Compared with their peers without PCa, elderly PCa survivors had a two-fold to five-fold greater prevalence of urinary incontinence, which rose with increasing survivorship duration. Observation, surgery, and ADT were each associated with increased urinary bother. These data suggest a substantially greater burden of urinary health problems among elderly PCa survivors than previously recognized. PMID:23587870

TALEN-engineered AR gene rearrangements reveal endocrine uncoupling of androgen receptor in prostate cancer

PubMed Central

Nyquist, Michael D.; Li, Yingming; Hwang, Tae Hyun; Manlove, Luke S.; Vessella, Robert L.; Silverstein, Kevin A. T.; Voytas, Daniel F.; Dehm, Scott M.

2013-01-01

Androgen receptor (AR) target genes direct development and survival of the prostate epithelial lineage, including prostate cancer (PCa). Thus, endocrine therapies that inhibit the AR ligand-binding domain (LBD) are effective in treating PCa. AR transcriptional reactivation is central to resistance, as evidenced by the efficacy of AR retargeting in castration-resistant PCa (CRPC) with next-generation endocrine therapies abiraterone and enzalutamide. However, resistance to abiraterone and enzalutamide limits this efficacy in most men, and PCa remains the second-leading cause of male cancer deaths. Here we show that AR gene rearrangements in CRPC tissues underlie a completely androgen-independent, yet AR-dependent, resistance mechanism. We discovered intragenic AR gene rearrangements in CRPC tissues, which we modeled using transcription activator-like effector nuclease (TALEN)-mediated genome engineering. This modeling revealed that these AR gene rearrangements blocked full-length AR synthesis, but promoted expression of truncated AR variant proteins lacking the AR ligand-binding domain. Furthermore, these AR variant proteins maintained the constitutive activity of the AR transcriptional program and a CRPC growth phenotype independent of full-length AR or androgens. These findings demonstrate that AR gene rearrangements are a unique resistance mechanism by which AR transcriptional activity can be uncoupled from endocrine regulation in CRPC. PMID:24101480

phzO, a Gene for Biosynthesis of 2-Hydroxylated Phenazine Compounds in Pseudomonas aureofaciens 30-84

PubMed Central

Delaney, Shannon M.; Mavrodi, Dmitri V.; Bonsall, Robert F.; Thomashow, Linda S.

2001-01-01

Certain strains of root-colonizing fluorescent Pseudomonas spp. produce phenazines, a class of antifungal metabolites that can provide protection against various soilborne root pathogens. Despite the fact that the phenazine biosynthetic locus is highly conserved among fluorescent Pseudomonas spp., individual strains differ in the range of phenazine compounds they produce. This study focuses on the ability of Pseudomonas aureofaciens 30-84 to produce 2-hydroxyphenazine-1-carboxylic acid (2-OH-PCA) and 2-hydroxyphenazine from the common phenazine metabolite phenazine-1-carboxylic acid (PCA). P. aureofaciens 30-84 contains a novel gene located downstream from the core phenazine operon that encodes a 55-kDa aromatic monooxygenase responsible for the hydroxylation of PCA to produce 2-OH-PCA. Knowledge of the genes responsible for phenazine product specificity could ultimately reveal ways to manipulate organisms to produce multiple phenazines or novel phenazines not previously described. PMID:11114932

Developing and Evaluating Creativity Gamification Rehabilitation System: The Application of PCA-ANFIS Based Emotions Model

ERIC Educational Resources Information Center

Su, Chung-Ho; Cheng, Ching-Hsue

2016-01-01

This study aims to explore the factors in a patient's rehabilitation achievement after a total knee replacement (TKR) patient exercises, using a PCA-ANFIS emotion model-based game rehabilitation system, which combines virtual reality (VR) and motion capture technology. The researchers combine a principal component analysis (PCA) and an adaptive…

Prolactin- and testosterone-induced carboxypeptidase-D correlates with increased nitrotyrosines and Ki67 in prostate cancer.

PubMed

Thomas, Lynn N; Merrimen, Jennifer; Bell, David G; Rendon, Ricardo; Too, Catherine K L

2015-11-01

Carboxypeptidase-D (CPD) cleaves C-terminal arginine for conversion to nitric oxide (NO) by nitric oxide synthase (NOS). Prolactin (PRL) and androgens stimulate CPD gene transcription and expression, which increases intracellular production of NO to promote viability of prostate cancer (PCa) cells in vitro. The current study evaluated whether hormonal upregulation of CPD and NO promote PCa cell viabilty in vivo, by correlating changes in expression of CPD and nitrotyrosine residues (products of NO action) with proliferation marker Ki67 and associated proteins during PCa development and progression. Fresh prostate tissues, obtained from 40 men with benign prostatic hyperplasia (BPH) or PCa, were flash-frozen at the time of surgery and used for RT-qPCR analysis of CPD, androgen receptor (AR), PRL receptor (PRLR), eNOS, and Ki67 levels. Archival paraffin-embedded tissues from 113 men with BPH or PCa were used for immunohistochemical (IHC) analysis of CPD, nitrotyrosines, phospho-Stat5 (for activated PRLR), AR, eNOS/iNOS, and Ki67. RT-qPCR and IHC analyses showed strong AR and PRLR expression in benign and malignant prostates. CPD mRNA levels increased ∼threefold in PCa compared to BPH, which corresponded to a twofold increase in Ki67 mRNA levels. IHC analysis showed a progressive increase in CPD from 11.4 ± 2.1% in benign to 21.8 ± 3.2% in low-grade (P = 0.007), 40.7 ± 4.0% in high-grade (P < 0.0001) and 50.0 ± 9.5% in castration-recurrent PCa (P < 0.0001). Immunostaining for nitrotyrosines and Ki67 mirrored these increases during PCa progression. CPD, nitrotyrosines, and Ki67 tended to co-localize, as did phospho-Stat5. CPD, nitrotyrosine, and Ki67 levels were higher in PCa than in benign and tended to co-localize, along with phospho-Stat5. The strong correlation in expression of these proteins in benign and malignant prostate tissues, combined with abundant AR and PRLR, supports in vitro evidence that the CPD-Arg-NO pathway is involved in the regulation of PCa cell proliferation. It further highlights a role for PRL in the development and progression of PCa. © 2015 Wiley Periodicals, Inc.

Nanostructures formed by cyclodextrin covered procainamide through supramolecular self assembly - Spectral and molecular modeling study

NASA Astrophysics Data System (ADS)

Rajendiran, N.; Mohandoss, T.; Sankaranarayanan, R. K.

2015-02-01

Inclusion complexation behavior of procainamide (PCA) with two cyclodextrins (α-CD and β-CD) were analyzed by absorption, fluorescence, scanning electron microscope (SEM), transmission electron microscope (TEM), Raman image, FT-IR, differential scanning colorimeter (DSC), Powder X ray diffraction (XRD) and 1H NMR. Blue shift was observed in β-CD whereas no significant spectral shift observed in α-CD. The inclusion complex formation results suggest that water molecules also present in the inside of the CD cavity. The present study revealed that the phenyl ring of the PCA drug is entrapped in the CD cavity. Cyclodextrin studies show that PCA forms 1:2 inclusion complex with α-CD and β-CD. PCA:α-CD complex form nano-sized particles (46 nm) and PCA:β-CD complex form self-assembled to micro-sized tubular structures. The shape-shifting of 2D nanosheets into 1D microtubes by simple rolling mechanism were analysed by micro-Raman and TEM images. Thermodynamic parameters (ΔH, ΔG and ΔS) of inclusion process were determined from semiempirical PM3 calculations.

Detection of compatibility between baclofen and excipients with aid of infrared spectroscopy and chemometry

NASA Astrophysics Data System (ADS)

Rojek, Barbara; Wesolowski, Marek; Suchacz, Bogdan

2013-12-01

In the paper infrared (IR) spectroscopy and multivariate exploration techniques: principal component analysis (PCA) and cluster analysis (CA) were applied as supportive methods for the detection of physicochemical incompatibilities between baclofen and excipients. In the course of research, the most useful rotational strategy in PCA proved to be varimax normalized, while in CA Ward's hierarchical agglomeration with Euclidean distance measure enabled to yield the most interpretable results. Chemometrical calculations confirmed the suitability of PCA and CA as the auxiliary methods for interpretation of infrared spectra in order to recognize whether compatibilities or incompatibilities between active substance and excipients occur. On the basis of IR spectra and the results of PCA and CA it was possible to demonstrate that the presence of lactose, β-cyclodextrin and meglumine in binary mixtures produce interactions with baclofen. The results were verified using differential scanning calorimetry, differential thermal analysis, thermogravimetry/differential thermogravimetry and X-ray powder diffraction analyses.

Free-energy landscape of RNA hairpins constructed via dihedral angle principal component analysis.

PubMed

Riccardi, Laura; Nguyen, Phuong H; Stock, Gerhard

2009-12-31

To systematically construct a low-dimensional free-energy landscape of RNA systems from a classical molecular dynamics simulation, various versions of the principal component analysis (PCA) are compared: the cPCA using the Cartesian coordinates of all atoms, the dPCA using the sine/cosine-transformed six backbone dihedral angles as well as the glycosidic torsional angle chi and the pseudorotational angle P, the aPCA which ignores the circularity of the 6 + 2 dihedral angles of the RNA, and the dPCA(etatheta), which approximates the 6 backbone dihedral angles by 2 pseudotorsional angles eta and theta. As representative examples, a 10-nucleotide UUCG hairpin and the 36-nucleotide segment SL1 of the Psi site of HIV-1 are studied by classical molecular dynamics simulation, using the Amber all-atom force field and explicit solvent. It is shown that the conformational heterogeneity of the RNA hairpins can only be resolved by an angular PCA such as the dPCA but not by the cPCA using Cartesian coordinates. Apart from possible artifacts due to the coupling of overall and internal motion, this is because the details of hydrogen bonding and stacking interactions but also of global structural rearrangements of the RNA are better discriminated by dihedral angles. In line with recent experiments, it is found that the free energy landscape of RNA hairpins is quite rugged and contains various metastable conformational states which may serve as an intermediate for unfolding.

Exercise and prostate cancer: From basic science to clinical applications.

PubMed

Campos, Christian; Sotomayor, Paula; Jerez, Daniel; González, Javier; Schmidt, Camila B; Schmidt, Katharina; Banzer, Winfried; Godoy, Alejandro S

2018-06-01

Prostate cancer (PCa) is a disease of increasing medical significance worldwide. In developed countries, PCa is the most common non-skin cancer in men, and one of the leading causes of cancer-related deaths. Exercise is one of the environmental factors that have been shown to influence cancer risk. Moreover, systemic reviews and meta-analysis have suggested that total physical activity is related to a decrease in the risk of developing PCa. In addition, epidemiological studies have shown that exercise, after diagnosis, has benefits regarding PCa development, and positive outcome in patients under treatment. The standard treatment for locally advanced or metastatic PCa is Androgen deprivation therapy (ADT). ADT produces diverse side effects, including loss of libido, changes in body composition (increase abdominal fat), and reduced muscle mass, and muscle tone. Analysis of numerous research publications showed that aerobic and/or resistance training improve patient's physical condition, such us, cardiorespiratory fitness, muscle strength, physical function, body composition, and fatigue. Therefore, exercise might counteract several ADT treatment-induced side effects. In addition of the aforementioned benefits, epidemiological, and in vitro studies have shown that exercise might decrease PCa development. Thus, physical activity might attenuate the risk of PCa and supervised exercise intervention might improve deleterious effects of cancer treatment, such as ADT side effects. This review article provides evidence indicating that exercise could complement, and potentiate, the current standard treatments for advanced PCa, probably by creating an unfavorable microenvironment that can negatively affect tumor development, and progression. © 2018 Wiley Periodicals, Inc.

1H nuclear magnetic resonance-based metabolomic characterization of wines by grape varieties and production areas.

PubMed

Son, Hong-Seok; Kim, Ki Myong; van den Berg, Frans; Hwang, Geum-Sook; Park, Won-Mok; Lee, Cherl-Ho; Hong, Young-Shick

2008-09-10

(1)H NMR spectroscopy was used to investigate the metabolic differences in wines produced from different grape varieties and different regions. A significant separation among wines from Campbell Early, Cabernet Sauvignon, and Shiraz grapes was observed using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The metabolites contributing to the separation were assigned to be 2,3-butanediol, lactate, acetate, proline, succinate, malate, glycerol, tartarate, glucose, and phenolic compounds by PCA and PLS-DA loading plots. Wines produced from Cabernet Sauvignon grapes harvested in the continental areas of Australia, France, and California were also separated. PLS-DA loading plots revealed that the level of proline in Californian Cabernet Sauvignon wines was higher than that in Australian and French Cabernet Sauvignon, Australian Shiraz, and Korean Campbell Early wines, showing that the chemical composition of the grape berries varies with the variety and growing area. This study highlights the applicability of NMR-based metabolomics with multivariate statistical data sets in determining wine quality and product origin.

Variation in cooking and eating quality traits in Japanese rice germplasm accessions

PubMed Central

Hori, Kiyosumi; Suzuki, Keitaro; Iijima, Ken; Ebana, Kaworu

2016-01-01

The eating quality of cooked rice is important and determines its market price and consumer acceptance. To comprehensively describe the variation of eating quality in 183 rice germplasm accessions, we evaluated 33 eating-quality traits including amylose and protein contents, pasting properties of rice flour, and texture of cooked rice grains. All eating-quality traits varied widely in the germplasm accessions. Principal-components analysis (PCA) revealed that allelic differences in the Wx gene explained the largest proportion of phenotypic variation of the eating-quality traits. In 146 accessions of non-glutinous temperate japonica rice, PCA revealed that protein content and surface texture of the cooked rice grains significantly explained phenotypic variations of the eating-quality traits. An allelic difference based on simple sequence repeats, which was located near a quantitative trait locus (QTL) on the short arm of chromosome 3, was associated with differences in the eating quality of non-glutinous temperate japonica rice. These results suggest that eating quality is controlled by genetic factors, including the Wx gene and the QTL on chromosome 3, in Japanese rice accessions. These genetic factors have been consciously selected for eating quality during rice breeding programs in Japan. PMID:27162502

Variation in cooking and eating quality traits in Japanese rice germplasm accessions.

PubMed

Hori, Kiyosumi; Suzuki, Keitaro; Iijima, Ken; Ebana, Kaworu

2016-03-01

The eating quality of cooked rice is important and determines its market price and consumer acceptance. To comprehensively describe the variation of eating quality in 183 rice germplasm accessions, we evaluated 33 eating-quality traits including amylose and protein contents, pasting properties of rice flour, and texture of cooked rice grains. All eating-quality traits varied widely in the germplasm accessions. Principal-components analysis (PCA) revealed that allelic differences in the Wx gene explained the largest proportion of phenotypic variation of the eating-quality traits. In 146 accessions of non-glutinous temperate japonica rice, PCA revealed that protein content and surface texture of the cooked rice grains significantly explained phenotypic variations of the eating-quality traits. An allelic difference based on simple sequence repeats, which was located near a quantitative trait locus (QTL) on the short arm of chromosome 3, was associated with differences in the eating quality of non-glutinous temperate japonica rice. These results suggest that eating quality is controlled by genetic factors, including the Wx gene and the QTL on chromosome 3, in Japanese rice accessions. These genetic factors have been consciously selected for eating quality during rice breeding programs in Japan.

Evaluation of serum prolidase activity and oxidative stress markers in men with BPH and prostate cancer.

PubMed

Kucukdurmaz, Faruk; Efe, Erkan; Çelik, Ahmet; Dagli, Hasan; Kılınc, Metin; Resim, Sefa

2017-12-12

Prostate cancer (PCa) and benign prostatic hyperplasia (BPH) are diseases of elderly men and are related to increased oxidative stress (OS). Although prolidase has a role in collagen metabolism, it is also used to evaluate OS in many diseases. However, there is a lack of data about serum prolidase activity (SPA) in prostate cancer. The aim of this study was to evaluate and compare SPA levels in males with BPH and PCa. Evaluation was made of a total of 81 men who underwent transrectal ultrasound guided prostate biopsy for a definitive diagnosis due to high PSA levels. Patients were separated into 2 groups as BPH and PCa patients. Pre-biopsy malondialdehyde (MDA), superoxide dismutase (SOD), PSA levels and serum prolidase activities (SPA) were compared between the groups and the correlations of SPA with the other parameters were also investigated in both groups. BPH was diagnosed in 51 patients and PCa in 30. The mean age of patients was similar in both groups as 63.25 ± 5.81 years in the BPH group 65.30 ± 7.35 years in the PCa group(p:0.081). The median MDA and SOD levels were insignificantly increased in the PCa patients. SPA values were similar in BPH and PCa patients. SPA did not correlate with age, PSA, MDA or SOD levels in either group. Our study results revealed that serum prolidase activity is similar in BPH and PCa cases and is not correlated with MDA, SOD or PSA levels.

Prognostic value of transformer 2β expression in prostate cancer.

PubMed

Diao, Yan; Wu, Dong; Dai, Zhijun; Kang, Huafeng; Wang, Ziming; Wang, Xijing

2015-01-01

Deregulation of transformer 2β (Tra2β) has been implicated in several cancers. However, the role of Tra2β expression in prostate cancer (PCa) is unclear. Therefore, this study was to investigate the expression of Tra2β in PCa and evaluated its association with clinicopathological variables and prognosis. Thirty paired fresh PCa samples were analyzed for Tra2β expression by Western blot analysis. Immunohistochemistry (IHC) assay was performed in 160 PCa samples after radical prostatectomy and adjacent non-cancerous tissues. Tra2β protein expression was divided into high expression group and low expression group by IHC. We also investigated the association of Tra2β expression with clinical and pathologic parameters. Kaplan-Meier plots and Cox proportional hazards regression model were used to analyze the association between Tra2β protein expression and prognosis of PCa patients. Our results showed that Tra2β was significantly upregulated in PCa tissues by western blot and IHC. Our data indicated that high expression of Tra2β was significantly associated with lymph node metastasis (P=0.002), clinical stage (P=0.015), preoperative prostate-specific antigen (P=0.003), Gleason score (P=0.001), and biochemical recurrence (P=0.021). High Tra2β expression was a significant predictor of poor biochemical recurrence free survival and overall survival both in univariate and multivariate analysis. We show that Tra2β was significantly upregulated in PCa patients after radical prostatectomy, and multivariate analysis confirmed Tra2β as an independent prognostic factor.

The theoretical and experimental study on dicalcium phosphate dehydrate loading with protocatechuic aldehyde.

PubMed

Guo, Yuehua; Qu, Shuxin; Lu, Xiong; Xie, Haodong; Zhang, Hongping; Weng, Jie

2010-07-01

The aim of this study is to investigate the interaction between dicalcium phosphate dihydrate (CaHPO(4) x 2H(2)O, DCPD) and Protocatechuic aldehyde (C(7)H(6)O(3), Pca), which is the water-soluble constituents of Chinese Medicine, Salvia Miltiorrhiza Bunge (SMB), by calculating the absorption energy through molecular dynamics simulation. Furthermore, the effects of functional groups of Pca and temperature on Pca adsorbed by DCPD are calculated respectively. DCPD/Pca and DCPD were analyzed by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TG). The simulation results showed that Pca mostly absorbed on the (0 2 0) surface of DCPD. The aldehyde group of Pca played a moren important role on the adsorption of Pca on DCPD than hydroxyl did, while temperature had no distinct effects on the adsorption. XRD results indicated that Pca induced the preferential growth of (0 2 0) crystal surface in DCPC/Pca whereas it had no influence on the crystal structure, the crystallinity and grain size of DCPD. FTIR and TG results showed that the characteristic peak of Pca was at 1295 cm(-1) and the content of Pca in DCPD was 16%, respectively. The present results show that molecular dynamics simulation is a very effective and complementary method to study the interaction between materials and medicine.

Dysregulated fibronectin trafficking by Hsp90 inhibition restricts prostate cancer cell invasion.

PubMed

Armstrong, Heather K; Gillis, Joanna L; Johnson, Ian R D; Nassar, Zeyad D; Moldovan, Max; Levrier, Claire; Sadowski, Martin C; Chin, Mei Yieng; Tomlinson Guns, Emma S; Tarulli, Gerard; Lynn, David J; Brooks, Douglas A; Selth, Luke A; Centenera, Margaret M; Butler, Lisa M

2018-02-01

The molecular chaperone Hsp90 is overexpressed in prostate cancer (PCa) and is responsible for the folding, stabilization and maturation of multiple oncoproteins, which are implicated in PCa progression. Compared to first-in-class Hsp90 inhibitors such as 17-allylamino-demethoxygeldanamycin (17-AAG) that were clinically ineffective, second generation inhibitor AUY922 has greater solubility and efficacy. Here, transcriptomic and proteomic analyses of patient-derived PCa explants identified cytoskeletal organization as highly enriched with AUY922 treatment. Validation in PCa cell lines revealed that AUY922 caused marked alterations to cell morphology, and suppressed cell motility and invasion compared to vehicle or 17-AAG, concomitant with dysregulation of key extracellular matrix proteins such as fibronectin (FN1). Interestingly, while the expression of FN1 was increased by AUY922, FN1 secretion was significantly decreased. This resulted in cytosolic accumulation of FN1 protein within late endosomes, suggesting that AUY922 disrupts vesicular secretory trafficking pathways. Depletion of FN1 by siRNA knockdown markedly reduced the invasive capacity of PCa cells, phenocopying AUY922. These results highlight a novel mechanism of action for AUY922 beyond its established effects on cellular mitosis and survival and, furthermore, identifies extracellular matrix cargo delivery as a potential therapeutic target for the treatment of aggressive PCa.

MicroRNA-126 inhibits proliferation and metastasis in prostate cancer via regulation of ADAM9

PubMed Central

Hua, Yibo; Liang, Chao; Miao, Chenkui; Wang, Shangqian; Su, Shifeng; Shao, Pengfei; Liu, Bianjiang; Bao, Meiling; Zhu, Jundong; Xu, Aiming; Zhang, Jianzhong; Li, Jie; Wang, Zengjun

2018-01-01

The aberrant expression of microRNAs (miRs) has been identified to serve a crucial role in tumor progression. The present study aimed to evaluate the role of miR-126 in human prostate cancer (PCa). Firstly, miR-126 expression in prostate cancer tissues and cell lines was analyzed. A luciferase reporter assay and a rescue assay were performed, which identified ADAM metalloproteinase domain 9 (ADAM9) as the target gene of miR-126. Subsequently, Kaplan-Meier and log-rank analyses were used to investigate the association between ADAM9 expression and PCa prognosis. The results revealed that miR-126 expression was significantly downregulated in PCa tissues and cell lines. miR-126 overexpression was demonstrated to reduce PCa cell proliferation and metastasis, and to reverse the epithelial-mesenchymal transition process in vitro. In addition, as the target gene of miR-126, the upregulation of ADAM9 reestablished cell functions, including cell proliferation, migration and invasion. Patients with high ADAM9 expression levels exhibited a shorter biochemical recurrence-free survival time. In summary, miR-126 serves a role in the proliferation and metastasis of PCa cells, indicating that miR-126 and ADAM9 may represent potential biomarkers in the progression of advanced PCa, in addition to therapeutic targets. PMID:29805636

Biological Evaluation and Molecular Docking of Protocatechuic Acid from Hibiscus sabdariffa L. as a Potent Urease Inhibitor by an ESI-MS Based Method.

PubMed

Hassan, Sherif T S; Švajdlenka, Emil

2017-10-11

Studies on enzyme inhibition remain a crucial area in drug discovery since these studies have led to the discoveries of new lead compounds useful in the treatment of several diseases. In this study, protocatechuic acid (PCA), an active compound from Hibiscus sabdariffa L. has been evaluated for its inhibitory properties against jack bean urease (JBU) as well as its possible toxic effect on human gastric epithelial cells (GES-1). Anti-urease activity was evaluated by an Electrospray Ionization-Mass Spectrometry (ESI-MS) based method, while cytotoxicity was assayed by the MTT method. PCA exerted notable anti-JBU activity compared with that of acetohydroxamic acid (AHA), with IC 50 values of 1.7 and 3.2 µM, respectively. PCA did not show any significant cytotoxic effect on (GES-1) cells at concentrations ranging from 1.12 to 3.12 µM. Molecular docking study revealed high spontaneous binding ability of PCA to the active site of urease. Additionally, the anti-urease activity was found to be related to the presence of hydroxyl moieties of PCA. This study presents PCA as a natural urease inhibitor, which could be used safely in the treatment of diseases caused by urease-producing bacteria.

A two-stage linear discriminant analysis via QR-decomposition.

PubMed

Ye, Jieping; Li, Qi

2005-06-01

Linear Discriminant Analysis (LDA) is a well-known method for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional data, such as image and text classification. An intrinsic limitation of classical LDA is the so-called singularity problems; that is, it fails when all scatter matrices are singular. Many LDA extensions were proposed in the past to overcome the singularity problems. Among these extensions, PCA+LDA, a two-stage method, received relatively more attention. In PCA+LDA, the LDA stage is preceded by an intermediate dimension reduction stage using Principal Component Analysis (PCA). Most previous LDA extensions are computationally expensive, and not scalable, due to the use of Singular Value Decomposition or Generalized Singular Value Decomposition. In this paper, we propose a two-stage LDA method, namely LDA/QR, which aims to overcome the singularity problems of classical LDA, while achieving efficiency and scalability simultaneously. The key difference between LDA/QR and PCA+LDA lies in the first stage, where LDA/QR applies QR decomposition to a small matrix involving the class centroids, while PCA+LDA applies PCA to the total scatter matrix involving all training data points. We further justify the proposed algorithm by showing the relationship among LDA/QR and previous LDA methods. Extensive experiments on face images and text documents are presented to show the effectiveness of the proposed algorithm.

A comprehensive evaluation of CHEK2 germline mutations in men with prostate cancer.

PubMed

Wu, Yishuo; Yu, Hongjie; Zheng, S Lilly; Na, Rong; Mamawala, Mufaddal; Landis, Tricia; Wiley, Kathleen; Petkewicz, Jacqueline; Shah, Sameep; Shi, Zhuqing; Novakovic, Kristian; McGuire, Michael; Brendler, Charles B; Ding, Qiang; Helfand, Brian T; Carter, H Ballentine; Cooney, Kathleen A; Isaacs, William B; Xu, Jianfeng

2018-06-01

Germline mutations in CHEK2 have been associated with prostate cancer (PCa) risk. Our objective is to examine whether germline pathogenic CHEK2 mutations can differentiate risk of lethal from indolent PCa. A case-case study of 703 lethal PCa patients and 1455 patients with low-risk localized PCa of European, African, and Chinese origin was performed. Germline DNA samples from these patients were sequenced for CHEK2. Mutation carrier rates and their association with lethal PCa were analyzed using the Fisher exact test and Kaplan-Meier survival analysis. In the entire study population, 40 (1.85%) patients were identified as carrying one of 15 different germline CHEK2 pathogenic or likely pathogenic mutations. CHEK2 mutations were detected in 16 (2.28%) of 703 lethal PCa patients compared with 24 (1.65%) of 1455 low-risk PCa patients (P = 0.31). No association was found between CHEK2 mutation status and early-diagnosis or PCa-specific survival time. However, the most common mutation in CHEK2, c.1100delC (p.T367 fs), had a significantly higher carrier rate (1.28%) in lethal PCa patients than low-risk PCa patients of European American origin (0.16%), P = 0.0038. The estimated Odds Ratio of this mutation for lethal PCa was 7.86. The carrier rate in lethal PCa was also significantly higher than that (0.46%) in 32 461 non-Finnish European subjects from the Exome Aggregation Consortium (ExAC) (P = 0.01). While overall CHEK2 mutations were not significantly more common in men with lethal compared to low-risk PCa, the specific CHEK2 mutation, c.1100delC, appears to contribute to an increased risk of lethal PCa in European American men. © 2018 Wiley Periodicals, Inc.

Sparse principal component analysis in medical shape modeling

NASA Astrophysics Data System (ADS)

Sjöstrand, Karl; Stegmann, Mikkel B.; Larsen, Rasmus

2006-03-01

Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims at producing easily interpreted models through sparse loadings, i.e. each new variable is a linear combination of a subset of the original variables. One of the aims of using SPCA is the possible separation of the results into isolated and easily identifiable effects. This article introduces SPCA for shape analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA algorithm has been implemented using Matlab and is available for download. The general behavior of the algorithm is investigated, and strengths and weaknesses are discussed. The original report on the SPCA algorithm argues that the ordering of modes is not an issue. We disagree on this point and propose several approaches to establish sensible orderings. A method that orders modes by decreasing variance and maximizes the sum of variances for all modes is presented and investigated in detail.

Prediction of Protein Modification Sites of Pyrrolidone Carboxylic Acid Using mRMR Feature Selection and Analysis

PubMed Central

Zheng, Lu-Lu; Niu, Shen; Hao, Pei; Feng, KaiYan; Cai, Yu-Dong; Li, Yixue

2011-01-01

Pyrrolidone carboxylic acid (PCA) is formed during a common post-translational modification (PTM) of extracellular and multi-pass membrane proteins. In this study, we developed a new predictor to predict the modification sites of PCA based on maximum relevance minimum redundancy (mRMR) and incremental feature selection (IFS). We incorporated 727 features that belonged to 7 kinds of protein properties to predict the modification sites, including sequence conservation, residual disorder, amino acid factor, secondary structure and solvent accessibility, gain/loss of amino acid during evolution, propensity of amino acid to be conserved at protein-protein interface and protein surface, and deviation of side chain carbon atom number. Among these 727 features, 244 features were selected by mRMR and IFS as the optimized features for the prediction, with which the prediction model achieved a maximum of MCC of 0.7812. Feature analysis showed that all feature types contributed to the modification process. Further site-specific feature analysis showed that the features derived from PCA's surrounding sites contributed more to the determination of PCA sites than other sites. The detailed feature analysis in this paper might provide important clues for understanding the mechanism of the PCA formation and guide relevant experimental validations. PMID:22174779

A new statistical PCA-ICA algorithm for location of R-peaks in ECG.

PubMed

Chawla, M P S; Verma, H K; Kumar, Vinod

2008-09-16

The success of ICA to separate the independent components from the mixture depends on the properties of the electrocardiogram (ECG) recordings. This paper discusses some of the conditions of independent component analysis (ICA) that could affect the reliability of the separation and evaluation of issues related to the properties of the signals and number of sources. Principal component analysis (PCA) scatter plots are plotted to indicate the diagnostic features in the presence and absence of base-line wander in interpreting the ECG signals. In this analysis, a newly developed statistical algorithm by authors, based on the use of combined PCA-ICA for two correlated channels of 12-channel ECG data is proposed. ICA technique has been successfully implemented in identifying and removal of noise and artifacts from ECG signals. Cleaned ECG signals are obtained using statistical measures like kurtosis and variance of variance after ICA processing. This analysis also paper deals with the detection of QRS complexes in electrocardiograms using combined PCA-ICA algorithm. The efficacy of the combined PCA-ICA algorithm lies in the fact that the location of the R-peaks is bounded from above and below by the location of the cross-over points, hence none of the peaks are ignored or missed.

Variants on 8q24 and prostate cancer risk in Chinese population: a meta-analysis.

PubMed

Ren, Xiao-Qiang; Zhang, Jian-Guo; Xin, Shi-Yong; Cheng, Tao; Li, Liang; Ren, Wei-Hua

2015-01-01

Previous studies have identified 8q24 as an important region to prostate cancer (PCa) susceptibility. The aim of this study was to investigate the role of six genetic variants on 8q24 (rs1447295, A; rs6983267, G; rs6983561, C; rs7837688, T; rs10090154, T and rs16901979, A) on PCa risk in Chinese population. Online electronic databases were searched to retrieve related articles concerning the association between 8q24 variants and PCa risk in men of Chinese population published between 2000 and 2014. Odds ratio (ORs) with its 95% correspondence interval (CI) were employed to assess the strength of association. Total eleven case-control studies were screened out, including 2624 PCa patients and 2438 healthy controls. Our results showed that three risk alleles of rs1447295 A (OR=1.35, 95% CI=1.19-1.53, P<0.00001), rs6983561 C (C vs. A: OR=1.41, 95% CI=1.21-1.63, P<0.00001) and rs10090154 T (T vs. C: OR=1.48, 95% CI=1.22-1.80, P<0.00001) on8q24 were significantly associated with PCa risk in Chinese population. Furthermore, genotypes of rs1447295, AA+AC; rs6983561, CC+AC and CC; rs10090154, TT+TC; and rs16901979, AA were associated with PCa as well (P<0.01). No association was found between rs6983267, rs7837688 and PCa risk. In conclusions, variants including rs1447295, rs6983561, rs10090154 and rs16901979 on 8q24 might be associated with PCa risk in Chinese population, indicating these four variations may contribute risk to this disease. This meta-analysis was the first study to assess the role of 8q24 variants on PCa risk in Chinese population.

An Estimate of the Incidence of Prostate Cancer in Africa: A Systematic Review and Meta-Analysis

PubMed Central

Aderemi, Adewale Victor; Iseolorunkanmi, Alexander; Oyedokun, Ayo; Ayo, Charles K.

2016-01-01

Background Prostate cancer (PCa) is rated the second most common cancer and sixth leading cause of cancer deaths among men globally. Reports show that African men suffer disproportionately from PCa compared to men from other parts of the world. It is still quite difficult to accurately describe the burden of PCa in Africa due to poor cancer registration systems. We systematically reviewed the literature on prostate cancer in Africa and provided a continent-wide incidence rate of PCa based on available data in the region. Methods A systematic literature search of Medline, EMBASE and Global Health from January 1980 to June 2015 was conducted, with additional search of Google Scholar, International Association of Cancer Registries (IACR), International Agency for Research on Cancer (IARC), and WHO African region websites, for studies that estimated incidence rate of PCa in any African location. Having assessed quality and consistency across selected studies, we extracted incidence rates of PCa and conducted a random effects meta-analysis. Results Our search returned 9766 records, with 40 studies spreading across 16 African countries meeting our selection criteria. We estimated a pooled PCa incidence rate of 22.0 (95% CI: 19.93–23.97) per 100,000 population, and also reported a median incidence rate of 19.5 per 100,000 population. We observed an increasing trend in PCa incidence with advancing age, and over the main years covered. Conclusion Effective cancer registration and extensive research are vital to appropriately quantifying PCa burden in Africa. We hope our findings may further assist at identifying relevant gaps, and contribute to improving knowledge, research, and interventions targeted at prostate cancer in Africa. PMID:27073921

Decision tree and PCA-based fault diagnosis of rotating machinery

NASA Astrophysics Data System (ADS)

Sun, Weixiang; Chen, Jin; Li, Jiaqing

2007-04-01

After analysing the flaws of conventional fault diagnosis methods, data mining technology is introduced to fault diagnosis field, and a new method based on C4.5 decision tree and principal component analysis (PCA) is proposed. In this method, PCA is used to reduce features after data collection, preprocessing and feature extraction. Then, C4.5 is trained by using the samples to generate a decision tree model with diagnosis knowledge. At last the tree model is used to make diagnosis analysis. To validate the method proposed, six kinds of running states (normal or without any defect, unbalance, rotor radial rub, oil whirl, shaft crack and a simultaneous state of unbalance and radial rub), are simulated on Bently Rotor Kit RK4 to test C4.5 and PCA-based method and back-propagation neural network (BPNN). The result shows that C4.5 and PCA-based diagnosis method has higher accuracy and needs less training time than BPNN.

The influence of stigma on the quality of life for prostate cancer survivors.

PubMed

Wood, Andrew W; Barden, Sejal; Terk, Mitchell; Cesaretti, Jamie

2017-01-01

The purpose of the present study was to investigate the influence of stigma on prostate cancer (PCa) survivors' quality of life. Stigma for lung cancer survivors has been the focus of considerable research (Else-Quest & Jackson, 2014); however, gaps remain in understanding the experience of PCa stigma. A cross-sectional correlational study was designed to assess the incidence of PCa stigma and its influence on the quality of life of survivors. Eighty-five PCa survivors were administered survey packets consisting of a stigma measure, a PCa-specific quality of life measure, and a demographic survey during treatment of their disease. A linear regression analysis was conducted with the data received from PCa survivors. Results indicated that PCa stigma has a significant, negative influence on the quality of life for survivors (R 2 = 0.33, F(4, 80) = 11.53, p < 0.001). There were no statistically significant differences in PCa stigma based on demographic variables (e.g., race and age). Implications for physical and mental health practitioners and researchers are discussed.

Synchrotron IR microspectroscopy for protein structure analysis: Potential and questions

DOE PAGES

Yu, Peiqiang

2006-01-01

Synchrotron radiation-based Fourier transform infrared microspectroscopy (S-FTIR) has been developed as a rapid, direct, non-destructive, bioanalytical technique. This technique takes advantage of synchrotron light brightness and small effective source size and is capable of exploring the molecular chemical make-up within microstructures of a biological tissue without destruction of inherent structures at ultra-spatial resolutions within cellular dimension. To date there has been very little application of this advanced technique to the study of pure protein inherent structure at a cellular level in biological tissues. In this review, a novel approach was introduced to show the potential of the newly developed, advancedmore » synchrotron-based analytical technology, which can be used to localize relatively “pure“ protein in the plant tissues and relatively reveal protein inherent structure and protein molecular chemical make-up within intact tissue at cellular and subcellular levels. Several complex protein IR spectra data analytical techniques (Gaussian and Lorentzian multi-component peak modeling, univariate and multivariate analysis, principal component analysis (PCA), and hierarchical cluster analysis (CLA) are employed to relatively reveal features of protein inherent structure and distinguish protein inherent structure differences between varieties/species and treatments in plant tissues. By using a multi-peak modeling procedure, RELATIVE estimates (but not EXACT determinations) for protein secondary structure analysis can be made for comparison purpose. The issues of pro- and anti-multi-peaking modeling/fitting procedure for relative estimation of protein structure were discussed. By using the PCA and CLA analyses, the plant molecular structure can be qualitatively separate one group from another, statistically, even though the spectral assignments are not known. The synchrotron-based technology provides a new approach for protein structure research in biological tissues at ultraspatial resolutions.« less

Evaluation of Vitronectin Expression in Prostate Cancer and the Clinical Significance of the Association of Vitronectin Expression with Prostate Specific Antigen in Detecting Prostate Cancer.

PubMed

Niu, Yue; Zhang, Ling; Bi, Xing; Yuan, Shuai; Chen, Peng

2016-03-05

To detect the expression of vitronectin (VTN) in the tissues and blood serum of prostate cancer (PCa) patients, and evaluate its clinical significance and to evaluate the significance of the combined assay of VTN and prostate specific antigens (PSA) in PCa diagnosis. To detect the expression of VTN as a potential marker for PCa diagnosis and prognosis, immunohistochemistry was performed on the tissues of 32 patients with metastatic PCa (PCaM), 34 patients with PCa without metastasis (PCa), and 41 patients with benign prostatic hyperplasia (BPH). The sera were then subjected to Western blot analysis. All cases were subsequently examined to determine the concentrations of PSA and VTN in the sera. The collected data were collated and analyzed. The positive expression rates of VTN in the tissues of the BPH and PCa groups (including PCa and PCaM groups) were 75.61% and 45.45%, respectively (P = .005). VTN was more highly expressed in the sera of the BPH patients (0.83 ± 0.07) than in the sera of the PCa patients (0.65 ± 0.06) (P < .05). It was also more highly expressed in the sera of the PCa patients than in the sera of the PCaM patients (0.35 ± 0.08) (P < .05). In the diagnosis of BPH and PCa, the Youden indexes of PSA detection, VTN detection, and combined detection were 0.2620, 0.3468, and 0.5635; the kappa values were 0.338, 0.304, and 0.448, respectively, and the areas under the receiver operating characteristic curve were 0.625, 0.673, and 0.703 (P < .05), respectively. VTN levels in sera may be used as a potential marker of PCa for the diagnosis and assessment of disease progression and metastasis. The combined detection of VTN and PSA in sera can be clinically applied in PCa diagnosis. .

Spatial and temporal assessment of surface water quality in the Arka River, Akkar, Lebanon.

PubMed

Daou, Claude; Nabbout, Rony; Kassouf, Amine

2016-12-01

Surface water quality monitoring constitutes a crucial and important step in any water quality management system. Twenty-three physicochemical and microbiological parameters were assessed in surface water samples collected from the Arka River located in the Akkar District, north of Lebanon. Eight sampling locations were considered along the river and seven sampling campaigns were performed in order to evaluate spatial and temporal influences. The extraction of relevant information from this relatively large data set was done using principal component analysis (PCA), being a very well established chemometric tool in this field. In a first step, extracted PCA loadings revealed the implication of several physicochemical parameters in the discriminations and trends highlighted by PCA scores, mainly due to soil leaching and seawater intrusion. However, further investigations showed the implication of organic and bacterial parameters in the discrimination of stations in the Akkar flatland. These discriminations probably refer to anthropogenic pollution coming from the agricultural area and the surrounding villages. Specific ultraviolet absorption (SUVA) indices confirmed these findings since values decreased for samples collected across the villages and the flatland, indicating an increase in anthropogenic dissolved organic matter. This study will hopefully help the national and local authorities to ameliorate the surface water quality management, enabling its proper use for irrigation purposes.

A stable systemic risk ranking in China's banking sector: Based on principal component analysis

NASA Astrophysics Data System (ADS)

Fang, Libing; Xiao, Binqing; Yu, Honghai; You, Qixing

2018-02-01

In this paper, we compare five popular systemic risk rankings, and apply principal component analysis (PCA) model to provide a stable systemic risk ranking for the Chinese banking sector. Our empirical results indicate that five methods suggest vastly different systemic risk rankings for the same bank, while the combined systemic risk measure based on PCA provides a reliable ranking. Furthermore, according to factor loadings of the first component, PCA combined ranking is mainly based on fundamentals instead of market price data. We clearly find that price-based rankings are not as practical a method as fundamentals-based ones. This PCA combined ranking directly shows systemic risk contributions of each bank for banking supervision purpose and reminds banks to prevent and cope with the financial crisis in advance.

Snake (Walterinnesia aegyptia) venom-loaded silica nanoparticles induce apoptosis and growth arrest in human prostate cancer cells.

PubMed

Badr, Gamal; Al-Sadoon, Mohamed K; Rabah, Danny M; Sayed, Douaa

2013-03-01

Prostate cancer (PCa) is the most commonly diagnosed cancer in men. The progression and invasion of PCa are normally mediated by the overexpression of chemokine receptors (CKRs) and the interaction between CKRs and their cognate ligands. We recently demonstrated that venom extracted from Walterinnesia aegyptia (WEV) either alone or in combination with silica nanoparticles (WEV+NP) mediated the growth arrest and apoptosis of breast cancer cells. In the present study, we evaluated the impact of WEV alone and WEV+NP on the migration, invasion, proliferation and apoptosis of prostate cancer cells. We found that WEV alone and WEV+NP decreased the viability of all cell types tested (PCa cells isolated from patient samples, PC3 cells and LNCaP cells) using an MTT assay. The IC(50) values were determined to be 10 and 5 μg/mL for WEV alone and WEV+NP, respectively. WEV+NP decreased the surface expression of the CKRs CXCR3, CXCR4, CXCR5 and CXCR6 to a greater extent than WEV alone and subsequently reduced migration and the invasion response of the cells to the cognate ligands of the CKRs (CXCL10, CXCL12, CXCL13 and CXCL16, respectively). Using a CFSE proliferation assay, we found that WEV+NP strongly inhibited epidermal growth factor-mediated PCa cell proliferation. Furthermore, analysis of the cell cycle indicated that WEV+NP strongly altered the cell cycle of PCa cells and enhanced the induction of apoptosis. Finally, we demonstrated that WEV+NP robustly decreased the expression of anti-apoptotic effectors, such as B cell Lymphoma-2 (Bcl-2), B cell Lymphoma-extra large (Bcl-(XL)) and myeloid cell leukemia sequence-1 (Mcl-1), and increased the expression of pro-apoptotic effectors, such as Bcl-2 homologous antagonist/killer (Bak), Bcl-2-associated X protein (Bax) and Bcl-2-interacting mediator of cell death (Bim). WEV+NP also altered the membrane potential of mitochondria in the PCa cells. Our data reveal the potential of nanoparticle-sustained delivery of snake venom as effective treatments for prostate cancer.

Metabolomics driven analysis of artichoke leaf and its commercial products via UHPLC-q-TOF-MS and chemometrics.

PubMed

Farag, Mohamed A; El-Ahmady, Sherweit H; Elian, Fatma S; Wessjohann, Ludger A

2013-11-01

The demand to develop efficient and reliable analytical methods for the quality control of herbal medicines and nutraceuticals is on the rise, together with an increase in the legal requirements for safe and consistent levels of active principles. Here, we describe an ultra-high performance liquid chromatography method (UHPLC) coupled with quadrupole high resolution time of flight mass spectrometry (qTOF-MS) analysis for the comprehensive measurement of metabolites from three Cynara scolymus (artichoke) cultivars: American Green Globe, French Hyrious, and Egyptian Baladi. Under optimized conditions, 50 metabolites were simultaneously quantified and identified including: eight caffeic acid derivatives, six saponins, 12 flavonoids and 10 fatty acids. Principal component analysis (PCA) was used to define both similarities and differences among the three artichoke leaf cultivars. In addition, batches from seven commercially available artichoke market products were analysed and showed variable quality, particularly in caffeic acid derivatives, flavonoid and fatty acid contents. PCA analysis was able to discriminate between various preparations, including differentiation between various batches from the same supplier. To the best of our knowledge, this study provides the first approach utilizing UHPLC-MS based metabolite fingerprinting to reveal secondary metabolite compositional differences in artichoke leaf extracts. Copyright © 2013 Elsevier Ltd. All rights reserved.

Comparison of water extraction methods in Tibet based on GF-1 data

NASA Astrophysics Data System (ADS)

Jia, Lingjun; Shang, Kun; Liu, Jing; Sun, Zhongqing

2018-03-01

In this study, we compared four different water extraction methods with GF-1 data according to different water types in Tibet, including Support Vector Machine (SVM), Principal Component Analysis (PCA), Decision Tree Classifier based on False Normalized Difference Water Index (FNDWI-DTC), and PCA-SVM. The results show that all of the four methods can extract large area water body, but only SVM and PCA-SVM can obtain satisfying extraction results for small size water body. The methods were evaluated by both overall accuracy (OAA) and Kappa coefficient (KC). The OAA of PCA-SVM, SVM, FNDWI-DTC, PCA are 96.68%, 94.23%, 93.99%, 93.01%, and the KCs are 0.9308, 0.8995, 0.8962, 0.8842, respectively, in consistent with visual inspection. In summary, SVM is better for narrow rivers extraction and PCA-SVM is suitable for water extraction of various types. As for dark blue lakes, the methods using PCA can extract more quickly and accurately.

Prevalence of Mathematical and Visuospatial Learning Disabilities in Patients With Posterior Cortical Atrophy.

PubMed

Miller, Zachary A; Rosenberg, Lynne; Santos-Santos, Miguel A; Stephens, Melanie; Allen, Isabel E; Hubbard, H Isabel; Cantwell, Averill; Mandelli, Maria Luisa; Grinberg, Lea T; Seeley, William W; Miller, Bruce L; Rabinovici, Gil D; Gorno-Tempini, Maria Luisa

2018-06-01

Increased prevalence of language-based learning disabilities (LDs) has been previously reported in patients with primary progressive aphasia (PPA). This study hypothesized that patients with focal neurodegenerative syndromes outside the language network, such as posterior cortical atrophy (PCA), would have a higher rate of nonlanguage LDs, congruent with their mainly visuospatial presentation. To investigate the prevalence and type of LD (language and/or mathematical and visuospatial) in a large cohort of patients with PCA compared with patients with logopenic variant PPA (lvPPA) and amnestic Alzheimer disease (AD). This case-control study reviewed 279 medical records from a university-based clinic and research center for patients with neurodegenerative diseases for LD history, including patients with PCA (n = 95), patients with lvPPA (n = 84), and a matched cohort with amnestic AD (n = 100). No records were excluded. The study compared cognitive and neuroimaging features of patients with PCA with and without LDs. A review of the records of patients presenting from March 1, 1999, to August 31, 2014, revealed 95 PCA cases and 84 lvPPA cases. Then 100 patients with amnestic AD from this same period were chosen for comparison, matching against the groups for age, sex, and disease severity. Data analysis was performed from September 8, 2013, to November 6, 2017. Prevalence of total LD history and prevalence of language and mathematical or visuospatial LD history across all cohorts. A total of 179 atypical AD cases (95 with PCA and 84 with lvPPA) and 100 disease control cases (amnestic AD) were included in the study. The groups were not statistically different for mean (SD) age at first visit (PCA, 61.9 [7.0] years; lvPPA, 65.1 [8.7] years; amnestic AD, 64.0 [12.6] years; P = .08), mean (SD) age at first symptom (PCA, 57.5 [7.0] years; lvPPA, 61.1 [9.0] years; amnestic AD, 59.6 [13.7] years; P = .06), or sex (PCA, 66.3% female; lvPPA, 56.0% female; amnestic AD, 57.0% female; P = .30) but differed on non-right-hand preference (PCA, 18.3%; lvPPA, 20.2%; amnestic AD, 7.7%; P = .04), race/ethnicity (PCA, 88.3% white; lvPPA, 99.0% white; amnestic AD, 80.0% white; P < .001), and mean (SD) educational level (PCA, 15.7 [3.2] years; lvPPA, 16.2 [3.3] years; amnestic AD, 14.8 [3.5] years; P = .02). A total of 18 of the 95 patients with PCA (18.9%) reported a history of LD, which is greater than the 3 of 100 patients (3.0%) in the amnestic AD cohort (P < .001) and the 10.0% expected rate in the general population (P = .007). In the PCA cohort, 13 of 95 patients (13.7%) had a nonlanguage mathematical and/or visuospatial LD; this rate was greater than that in the amnestic AD (1 of 100 [1.0%]; P < .001) and lvPPA (2 of 84 [2.4%]; P = .006) cohorts and greater than the 6.0% expected general population rate of mathematical LD (P = .003). Compared with the patients with PCA without LDs, the group with LDs had greater preservation of global cognition and a more right-lateralized pattern of atrophy. Nonlanguage mathematical and visuospatial LDs were associated with focal, visuospatial predominant neurodegenerative clinical syndromes. This finding supports the hypothesis that neurodevelopmental differences in specific brain networks are associated with phenotypic manifestation of later-life neurodegenerative disease.

Molecular Clustering Interrelationships and Carbohydrate Conformation in Hull and Seeds Among Barley Cultivars

DOE Office of Scientific and Technical Information (OSTI.GOV)

N Liu; P Yu

2011-12-31

The objective of this study was to use molecular spectral analyses with the diffuse reflectance Fourier transform infrared spectroscopy (DRIFT) bioanlytical technique to study carbohydrate conformation features, molecular clustering and interrelationships in hull and seed among six barley cultivars (AC Metcalfe, CDC Dolly, McLeod, CDC Helgason, CDC Trey, CDC Cowboy), which had different degradation kinetics in rumen. The molecular structure spectral analyses in both hull and seed involved the fingerprint regions of ca. 1536-1484 cm{sup -1} (attributed mainly to aromatic lignin semicircle ring stretch), ca. 1293-1212 cm{sup -1} (attributed mainly to cellulosic compounds in the hull), ca. 1269-1217 cm{sup -1}more » (attributed mainly to cellulosic compound in the seeds), and ca. 1180-800 cm{sup -1} (attributed mainly to total CHO C-O stretching vibrations) together with an agglomerative hierarchical cluster (AHCA) and principal component spectral analyses (PCA). The results showed that the DRIFT technique plus AHCA and PCA molecular analyses were able to reveal carbohydrate conformation features and identify carbohydrate molecular structure differences in both hull and seeds among the barley varieties. The carbohydrate molecular spectral analyses at the region of ca. 1185-800 cm{sup -1} together with the AHCA and PCA were able to show that the barley seed inherent structures exhibited distinguishable differences among the barley varieties. CDC Helgason had differences from AC Metcalfe, MeLeod, CDC Cowboy and CDC Dolly in carbohydrate conformation in the seed. Clear molecular cluster classes could be distinguished and identified in AHCA analysis and the separate ellipses could be grouped in PCA analysis. But CDC Helgason had no distinguished differences from CDC Trey in carbohydrate conformation. These carbohydrate conformation/structure difference could partially explain why the varieties were different in digestive behaviors in animals. The molecular spectroscopy technique used in this study could also be used for other plant-based feed and food structure studies.« less

MicroRNA profiling of novel African American and Caucasian Prostate Cancer cell lines reveals a reciprocal regulatory relationship of miR-152 and DNA methyltranferase 1

PubMed Central

Theodore, Shaniece C.; Davis, Melissa; Zhao, Fu; Wang, Honghe; Chen, Dongquan; Rhim, Johng; Dean-Colomb, Windy; Turner, Timothy; Ji, Weidong; Zeng, Guohua; Grizzle, William; Yates, Clayton

2014-01-01

miRNA expression in African American compared to Caucasian PCa patients has not been widely explored. Herein, we probed the miRNA expression profile of novel AA and CA derived prostate cancer cell lines. We found a unique miRNA signature associated with AA cell lines, independent of tumor status. Evaluation of the most differentially expressed miRNAs showed that miR-132, miR-367b, miR-410, and miR-152 were decreased in more aggressive cells, and this was reversed after treatment of the cells with 5-aza-2′-deoxycytidine. Sequencing of the miR-152 promoter confirmed that it was highly methylated. Ectopic expression of miR-152 resulted in decreased growth, migration, and invasion. Informatics analysis of a large patient cohort showed that decreased miR-152 expression correlated with increased metastasis and a decrease in biochemical recurrence free survival. Analysis of 39 prostate cancer tissues with matched controls (20 AA and 19 CA), showed that 50% of AA patients had statistically significant lower miR-152 expression compared to only 35% of CA patients. Ectopic expression of miR-152 in LNCaP, PC-3, and MDA-PCa-2b cells down-regulated DNA (cytosine-5)-methyltransferase 1 (DNMT1) through direct binding in the DNMT1 3'UTR. There appeared to be a reciprocal regulatory relationship of miR-152/DNMT1 expression, as cells treated with siRNA DNMT1 caused miR-152 to be re-expressed in all cell lines. In summary, these results demonstrate that epigenetic regulation of miR-152/DNMT1 may play an important role in multiple events that contribute to the aggressiveness of PCa tumors, with an emphasis on AA PCa patients. PMID:25004396

Combined serum and EPS-urine proteomic analysis using iTRAQ technology for discovery of potential prostate cancer biomarkers.

PubMed

Zhang, Mo; Chen, Lizhu; Yuan, Zhengwei; Yang, Zeyu; Li, Yue; Shan, Liping; Yin, Bo; Fei, Xiang; Miao, Jianing; Song, Yongsheng

2016-11-01

Prostate cancer (PCa) is one of the most common malignant tumors and a major cause of cancer-related death for men worldwide. The aim of our study was to identify potential non-invasive serum and expressed prostatic secretion (EPS)-urine biomarkers for accurate diagnosis of PCa. Here, we performed a combined isobaric tags for relative and absolute quantification (iTRAQ) proteomic analysis to compare protein profiles using pooled serum and EPS-urine samples from 4 groups of patients: benign prostate hyperplasia (BPH), high grade prostatic intraepithelial neoplasia (HGPIN), localized PCa and metastatic PCa. The differentially expressed proteins were rigorously selected and further validated in a large and independent cohort using classical ELISA and Western blot assays. Finally, we established a multiplex biomarker panel consisting of 3 proteins (serum PF4V1, PSA, and urinary CRISP3) with an excellent diagnostic capacity to differentiate PCa from BPH [area under the receiver operating characteristic curve (AUC) of 0.941], which showed an evidently greater discriminatory ability than PSA alone (AUC, 0.757) (P<0.001). Importantly, even when PSA level was in the gray zone (4-10 ng/mL), a combination of PF4V1 and CRISP3 could achieve a relatively high diagnostic efficacy (AUC, 0.895). Furthermore, their combination also had the potential to distinguish PCa from HGPIN (AUC, 0.934). Our results demonstrated that the combined application of serum and EPS-urine biomarkers can improve the diagnosis of PCa and provide a new prospect for non-invasive PCa detection.

An In Vitro Spectroscopic Analysis to Determine Whether para-Chloroaniline is Produced from Mixing Sodium Hypochlorite and Chlorhexidine

PubMed Central

Thomas, John E.; Sem, Daniel S.

2009-01-01

Introduction The purpose of this in vitro study was to determine whether para-chloroaniline (PCA) is formed through the reaction of mixing sodium hypochlorite (NaOCl) and chlorhexidine (CHX). Methods Initially commercially available samples of chlorhexidine acetate (CHXa) and PCA were analyzed with 1H NMR spectroscopy. Two solutions, NaOCl and CHXa, were warmed to 37°C and when mixed they produced a brown precipitate. This precipitate was separated in half and pure PCA was added to one of the samples for comparison before they were each analyzed with 1H NMR spectroscopy. Results The peaks in the 1H NMR spectra of CHXa and PCA were assigned to specific protons of the molecules, and the location of the aromatic peaks in the PCA spectrum defined the PCA doublet region. While the spectrum of the precipitate alone resulted in a complex combination of peaks, upon magnification there were no peaks in the PCA doublet region which were intense enough to be quantified. In the spectrum of the precipitate, to which PCA was added, two peaks do appear in the PCA doublet region. Comparing this spectrum to that of precipitate alone, the peaks in the PCA doublet region are not visible prior to the addition of PCA. Conclusions Based on this in vitro study, the reaction mixture of NaOCl and CHXa does not produce PCA at any measurable quantity and further investigation is needed to determine the chemical composition of the brown precipitate. PMID:20113799

Direct analysis in real time mass spectrometry and multivariate data analysis: a novel approach to rapid identification of analytical markers for quality control of traditional Chinese medicine preparation.

PubMed

Zeng, Shanshan; Wang, Lu; Chen, Teng; Wang, Yuefei; Mo, Huanbiao; Qu, Haibin

2012-07-06

The paper presents a novel strategy to identify analytical markers of traditional Chinese medicine preparation (TCMP) rapidly via direct analysis in real time mass spectrometry (DART-MS). A commonly used TCMP, Danshen injection, was employed as a model. The optimal analysis conditions were achieved by measuring the contribution of various experimental parameters to the mass spectra. Salvianolic acids and saccharides were simultaneously determined within a single 1-min DART-MS run. Furthermore, spectra of Danshen injections supplied by five manufacturers were processed with principal component analysis (PCA). Obvious clustering was observed in the PCA score plot, and candidate markers were recognized from the contribution plots of PCA. The suitability of potential markers was then confirmed by contrasting with the results of traditional analysis methods. Using this strategy, fructose, glucose, sucrose, protocatechuic aldehyde and salvianolic acid A were rapidly identified as the markers of Danshen injections. The combination of DART-MS with PCA provides a reliable approach to the identification of analytical markers for quality control of TCMP. Copyright © 2012 Elsevier B.V. All rights reserved.

Determining the amounts of urea and glucose in urine of patients with renal complications from diabetes mellitus and hypertension by near-infrared Raman spectroscopy

NASA Astrophysics Data System (ADS)

Bispo, Jeyse A. M.; Silveira, Landulfo; Vieira, Elzo E. d. S.; Fernandes, Adriana B.

2013-02-01

Diabetes mellitus and hypertension diseases are frequently found in the same patient, which if untreated predispose to atherosclerotic and kidney diseases. The objective of this study was to identify potential biomarkers in the urine of diabetic and hypertensive patients through dispersive near-infrared Raman spectroscopy. Urine samples were collected from patients with diabetes and hypertension but no complications (LG), high degree of complications (HG), and control ones: one fraction was submitted to biochemical tests and another one was stored frozen (-20°C) until spectral analysis. Samples were warmed up and placed in an aluminum sample holder for Raman spectra collection using a dispersive spectrometer (830 nm wavelength, 300 mW laser power and 20 s exposure time). Spectra were then submitted to Principal Components Analysis. The PCA loading vectors 1 and 3 revealed spectral features of urea/creatinine and glucose, respectively; the PCA scores showed that patients with diabetes/hypertension (LG and HG) had higher amount of glucose in the urine compared to the normal group (p < 0.05), which can bring serious consequences to patients. Also, the PCA scores showed that the amount of urea decreased in the groups with diabetes/hypertension (p < 0.05), which generates the same concern as it is a marker that has a strong importance in the metabolic changes induced by such diseases. These results, applied to the analysis of urine of patients with diabetes/hypertension, can lead to early diagnostic information of complications and a possible disease prognosis in the patients where no complications from diabetes and hypertension were found.

The Classroom Environment Questionnaire (CEQ): Development and preliminary structural validity.

PubMed

Lyons, Carissa; Brown, Ted; Bourke-Taylor, Helen

2018-04-16

Occupational therapists offer a unique perspective regarding the contribution of the environment to occupational performance. Therefore, a scale that measures the unique characteristics of the primary school classroom environment where children complete their daily schoolwork occupations is needed. The aim of this study was to develop and psychometrically evaluate a new teacher-report questionnaire that measures a number of environmental characteristics of primary school classrooms. Participants (N = 117) completed the Classroom Environment Questionnaire (CEQ), which utilises a 4-point Likert scale where teachers rate 51 environmental characteristics of their classroom. Teachers also rate the extent to which they believe the physical, social, temporal, institutional and cultural classroom environmental domains contribute to students' schoolwork performance using a 10-point scale. The structural validity of the CEQ was examined using principal component analysis (PCA). Inter-item correlations were examined using Pearson r correlations, while the internal consistency of the CEQ was assessed using Cronbach's alpha. PCA revealed the CEQ to be multidimensional, with 31 items loading onto nine viable factors, representing the unique nature of classroom environments. Based on the PCA results, 20 items were removed from the CEQ. Cronbach's alpha and correlation analysis indicated that most CEQ subsections had acceptable internal consistency (alpha range 0.70-0.82), with four subsections demonstrating a lower level of internal consistency (alpha range 0.55-0.69). Preliminary structural validity and internal consistency analysis findings confirm that the CEQ has potential to be a useful scale for professionals wishing to examine the unique characteristics of primary school classrooms that influence the occupational performance of students. Ongoing analyses will be undertaken to further explore the CEQ's validity and reliability. © 2018 Occupational Therapy Australia.

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars.

PubMed

Hu, Boran; Yue, Yaqing; Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W

2015-01-01

Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach.

PCA based clustering for brain tumor segmentation of T1w MRI images.

PubMed

Kaya, Irem Ersöz; Pehlivanlı, Ayça Çakmak; Sekizkardeş, Emine Gezmez; Ibrikci, Turgay

2017-03-01

Medical images are huge collections of information that are difficult to store and process consuming extensive computing time. Therefore, the reduction techniques are commonly used as a data pre-processing step to make the image data less complex so that a high-dimensional data can be identified by an appropriate low-dimensional representation. PCA is one of the most popular multivariate methods for data reduction. This paper is focused on T1-weighted MRI images clustering for brain tumor segmentation with dimension reduction by different common Principle Component Analysis (PCA) algorithms. Our primary aim is to present a comparison between different variations of PCA algorithms on MRIs for two cluster methods. Five most common PCA algorithms; namely the conventional PCA, Probabilistic Principal Component Analysis (PPCA), Expectation Maximization Based Principal Component Analysis (EM-PCA), Generalize Hebbian Algorithm (GHA), and Adaptive Principal Component Extraction (APEX) were applied to reduce dimensionality in advance of two clustering algorithms, K-Means and Fuzzy C-Means. In the study, the T1-weighted MRI images of the human brain with brain tumor were used for clustering. In addition to the original size of 512 lines and 512 pixels per line, three more different sizes, 256 × 256, 128 × 128 and 64 × 64, were included in the study to examine their effect on the methods. The obtained results were compared in terms of both the reconstruction errors and the Euclidean distance errors among the clustered images containing the same number of principle components. According to the findings, the PPCA obtained the best results among all others. Furthermore, the EM-PCA and the PPCA assisted K-Means algorithm to accomplish the best clustering performance in the majority as well as achieving significant results with both clustering algorithms for all size of T1w MRI images. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

[Analyzing and modeling methods of near infrared spectroscopy for in-situ prediction of oil yield from oil shale].

PubMed

Liu, Jie; Zhang, Fu-Dong; Teng, Fei; Li, Jun; Wang, Zhi-Hong

2014-10-01

In order to in-situ detect the oil yield of oil shale, based on portable near infrared spectroscopy analytical technology, with 66 rock core samples from No. 2 well drilling of Fuyu oil shale base in Jilin, the modeling and analyzing methods for in-situ detection were researched. By the developed portable spectrometer, 3 data formats (reflectance, absorbance and K-M function) spectra were acquired. With 4 different modeling data optimization methods: principal component-mahalanobis distance (PCA-MD) for eliminating abnormal samples, uninformative variables elimination (UVE) for wavelength selection and their combina- tions: PCA-MD + UVE and UVE + PCA-MD, 2 modeling methods: partial least square (PLS) and back propagation artificial neural network (BPANN), and the same data pre-processing, the modeling and analyzing experiment were performed to determine the optimum analysis model and method. The results show that the data format, modeling data optimization method and modeling method all affect the analysis precision of model. Results show that whether or not using the optimization method, reflectance or K-M function is the proper spectrum format of the modeling database for two modeling methods. Using two different modeling methods and four different data optimization methods, the model precisions of the same modeling database are different. For PLS modeling method, the PCA-MD and UVE + PCA-MD data optimization methods can improve the modeling precision of database using K-M function spectrum data format. For BPANN modeling method, UVE, UVE + PCA-MD and PCA- MD + UVE data optimization methods can improve the modeling precision of database using any of the 3 spectrum data formats. In addition to using the reflectance spectra and PCA-MD data optimization method, modeling precision by BPANN method is better than that by PLS method. And modeling with reflectance spectra, UVE optimization method and BPANN modeling method, the model gets the highest analysis precision, its correlation coefficient (Rp) is 0.92, and its standard error of prediction (SEP) is 0.69%.

Low-Molecular-Weight Protein Tyrosine Phosphatase Predicts Prostate Cancer Outcome by Increasing the Metastatic Potential.

PubMed

Ruela-de-Sousa, Roberta R; Hoekstra, Elmer; Hoogland, A Marije; Queiroz, Karla C Souza; Peppelenbosch, Maikel P; Stubbs, Andrew P; Pelizzaro-Rocha, Karin; van Leenders, Geert J L H; Jenster, Guido; Aoyama, Hiroshi; Ferreira, Carmen V; Fuhler, Gwenny M

2016-04-01

Low-risk patients suffering from prostate cancer (PCa) are currently placed under active surveillance rather than undergoing radical prostatectomy. However, clear parameters for selecting the right patient for each strategy are not available, and new biomarkers and treatment modalities are needed. Low-molecular-weight protein tyrosine phosphatase (LMWPTP) could present such a target. To correlate expression levels of LMWPTP in primary PCa to clinical outcome, and determine the role of LMWPTP in prostate tumor cell biology. Acid phosphatase 1, soluble (ACP1) expression was analyzed on microarray data sets, which were subsequently used in Ingenuity Pathway Analysis. Immunohistochemistry was performed on a tissue microarray containing material of 481 PCa patients whose clinicopathologic data were recorded. PCa cell line models were used to investigate the role of LMWPTP in cell proliferation, migration, adhesion, and anoikis resistance. The association between LMWPTP expression and clinical and pathologic outcomes was calculated using chi-square correlations and multivariable Cox regression analysis. Functional consequences of LMWPTP overexpression or downregulation were determined using migration and adhesion assays, confocal microscopy, Western blotting, and proliferation assays. LMWPTP expression was significantly increased in human PCa and correlated with earlier recurrence of disease (hazard ratio [HR]:1.99; p<0.001) and reduced patient survival (HR: 1.53; p=0.04). Unbiased Ingenuity analysis comparing cancer and normal prostate suggests migratory propensities in PCa. Indeed, overexpression of LMWPTP increases PCa cell migration, anoikis resistance, and reduces activation of focal adhesion kinase/paxillin, corresponding to decreased adherence. Overexpression of LMWPTP in PCa confers a malignant phenotype with worse clinical outcome. Prospective follow-up should determine the clinical potential of LMWPTP overexpression. These findings implicate low-molecular-weight protein tyrosine phosphatase as a novel oncogene in prostate cancer and could offer the possibility of using this protein as biomarker or target for treatment of this disease. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

The cascade construction of artificial ponds as a tool for urban stream restoration - The use of benthic diatoms to assess the effects of restoration practices.

PubMed

Żelazna-Wieczorek, Joanna; Nowicka-Krawczyk, Paulina

2015-12-15

A series of cascade artificial ponds were constructed to improve the ecological status of the stream. To evaluate the effects of restoration practices, a bioassessment, based on phytobenthic algae - the diatoms, was made. Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) of diatom assemblages allowed for evaluating the influence of a series of cascade artificial ponds on stream integrity. To reveal which environmental factors had the greatest influence on shaping diatom assemblages, the BIO-ENV procedure was used, and in order to examine whether these factors had equal influence on diatoms along the stream, Redundancy Analysis (RDA) was used. The analysis of diatom assemblages allowed for the calculation of the diatom indices in order to assess the water quality and the ecological status of the stream. Artificial ponds constructed on the stream had significant effects on the integrity of the stream ecosystem. Diatom assemblages characteristic of stream habitats were disrupted by the species from ponds. HCA and PCA revealed that the stream was clearly divided into three sections: ponds, stream parts under the influence of ponds, and stream parts isolated from ponds. The ponds thus altered stream environmental conditions. Benthic diatom assemblages were affected by a combination of four environmental factors: the concentration of ammonium ions, dissolved oxygen, conductivity, and the amount of total suspended material in the water. These factors, together with water pH, had a diverse influence on diatom assemblages alongside the stream, which was caused by a series of cascade ponds. In theory, this restoration practice should restore the stream close to its natural state, but bioassessment of the stream ecosystem based on diatoms revealed that there was no improvement of the ecological status alongside the stream. The construction of artificial ponds disrupted stream continuity and altered the character of the stream ecosystem. Copyright © 2015 Elsevier B.V. All rights reserved.

Contrast-Enhanced Ultrasound (CEUS) and Quantitative Perfusion Analysis in Patients with Suspicion for Prostate Cancer.

PubMed

Maxeiner, Andreas; Fischer, Thomas; Schwabe, Julia; Baur, Alexander Daniel Jacques; Stephan, Carsten; Peters, Robert; Slowinski, Torsten; von Laffert, Maximilian; Marticorena Garcia, Stephan Rodrigo; Hamm, Bernd; Jung, Ernst-Michael

2018-06-06

 The aim of this study was to investigate contrast-enhanced ultrasound (CEUS) parameters acquired by software during magnetic resonance imaging (MRI) US fusion-guided biopsy for prostate cancer (PCa) detection and discrimination.  From 2012 to 2015, 158 out of 165 men with suspicion for PCa and with at least 1 negative biopsy of the prostate were included and underwent a multi-parametric 3 Tesla MRI and an MRI/US fusion-guided biopsy, consecutively. CEUS was conducted during biopsy with intravenous bolus application of 2.4 mL of SonoVue ® (Bracco, Milan, Italy). In the latter CEUS clips were investigated using quantitative perfusion analysis software (VueBox, Bracco). The area of strongest enhancement within the MRI pre-located region was investigated and all available parameters from the quantification tool box were collected and analyzed for PCa and its further differentiation was based on the histopathological results.  The overall detection rate was 74 (47 %) PCa cases in 158 included patients. From these 74 PCa cases, 49 (66 %) were graded Gleason ≥ 3 + 4 = 7 (ISUP ≥ 2) PCa. The best results for cancer detection over all quantitative perfusion parameters were rise time (p = 0.026) and time to peak (p = 0.037). Within the subgroup analysis (> vs ≤ 3 + 4 = 7a (ISUP 2)), peak enhancement (p = 0.012), wash-in rate (p = 0.011), wash-out rate (p = 0.007) and wash-in perfusion index (p = 0.014) also showed statistical significance.  The quantification of CEUS parameters was able to discriminate PCa aggressiveness during MRI/US fusion-guided prostate biopsy. © Georg Thieme Verlag KG Stuttgart · New York.

Recruitment Methods and Show Rates to a Prostate Cancer Early Detection Program for High-Risk Men: A Comprehensive Analysis

PubMed Central

Giri, Veda N.; Coups, Elliot J.; Ruth, Karen; Goplerud, Julia; Raysor, Susan; Kim, Taylor Y.; Bagden, Loretta; Mastalski, Kathleen; Zakrzewski, Debra; Leimkuhler, Suzanne; Watkins-Bruner, Deborah

2009-01-01

Purpose Men with a family history (FH) of prostate cancer (PCA) and African American (AA) men are at higher risk for PCA. Recruitment and retention of these high-risk men into early detection programs has been challenging. We report a comprehensive analysis on recruitment methods, show rates, and participant factors from the Prostate Cancer Risk Assessment Program (PRAP), which is a prospective, longitudinal PCA screening study. Materials and Methods Men 35–69 years are eligible if they have a FH of PCA, are AA, or have a BRCA1/2 mutation. Recruitment methods were analyzed with respect to participant demographics and show to the first PRAP appointment using standard statistical methods Results Out of 707 men recruited, 64.9% showed to the initial PRAP appointment. More individuals were recruited via radio than from referral or other methods (χ2 = 298.13, p < .0001). Men recruited via radio were more likely to be AA (p<0.001), less educated (p=0.003), not married or partnered (p=0.007), and have no FH of PCA (p<0.001). Men recruited via referrals had higher incomes (p=0.007). Men recruited via referral were more likely to attend their initial PRAP visit than those recruited by radio or other methods (χ2 = 27.08, p < .0001). Conclusions This comprehensive analysis finds that radio leads to higher recruitment of AA men with lower socioeconomic status. However, these are the high-risk men that have lower show rates for PCA screening. Targeted motivational measures need to be studied to improve show rates for PCA risk assessment for these high-risk men. PMID:19758657

Study of force loss due to friction comparing two ceramic brackets during sliding tooth movement.

PubMed

AlSubaie, Mai; Talic, Nabeel; Khawatmi, Said; Alobeid, Ahmad; Bourauel, Christoph; El-Bialy, Tarek

2016-09-01

To compare the percentage of force loss generated during canine sliding movements in newly introduced ceramic brackets with metal brackets. Two types of ceramic brackets, namely polycrystalline alumina (PCA) ceramic brackets (Clarity Advanced) and monocrystalline alumina (MCA) ceramic brackets (Inspire Ice) were compared with stainless steel (SS) brackets (Victory Series). All bracket groups (n = 5 each) were for the maxillary canines and had a 0.018-inch slot size. The brackets were mounted on an Orthodontic Measurement and Simulation System (OMSS) to simulate the canine retraction movement into the first premolar extraction space. Using elastic ligatures, 0.016 × 0.022″ (0.40 × 0.56 mm) stainless steel archwires were ligated onto the brackets. Retraction force was applied via a nickel-titanium coil spring with a nearly constant force of approximately 1 N. The OMSS measured the percentage of force loss over the retraction path by referring to the difference between the applied retraction force and actual force acting on each bracket. Between group comparisons were done with one-way analysis of variance. The metal brackets revealed the lowest percentage of force loss due to friction, followed by the PCA and MCA ceramic bracket groups (67 ± 4, 68 ± 7, and 76 ± 3 %, respectively). There was no significant difference between SS and PCA brackets (p = 0.97), but we did observe significant differences between metal and MCA brackets (p = 0.03) and between PCA and MCA ceramic brackets (p = 0.04). PCA ceramic brackets, whose slot surface is covered with an yttria-stabilized zirconia-based coating exhibited frictional properties similar to those of metal brackets. Frictional resistance resulted in an over 60 % loss of the applied force due to the use of elastic ligatures.

Probabilistic PCA of censored data: accounting for uncertainties in the visualization of high-throughput single-cell qPCR data.

PubMed

Buettner, Florian; Moignard, Victoria; Göttgens, Berthold; Theis, Fabian J

2014-07-01

High-throughput single-cell quantitative real-time polymerase chain reaction (qPCR) is a promising technique allowing for new insights in complex cellular processes. However, the PCR reaction can be detected only up to a certain detection limit, whereas failed reactions could be due to low or absent expression, and the true expression level is unknown. Because this censoring can occur for high proportions of the data, it is one of the main challenges when dealing with single-cell qPCR data. Principal component analysis (PCA) is an important tool for visualizing the structure of high-dimensional data as well as for identifying subpopulations of cells. However, to date it is not clear how to perform a PCA of censored data. We present a probabilistic approach that accounts for the censoring and evaluate it for two typical datasets containing single-cell qPCR data. We use the Gaussian process latent variable model framework to account for censoring by introducing an appropriate noise model and allowing a different kernel for each dimension. We evaluate this new approach for two typical qPCR datasets (of mouse embryonic stem cells and blood stem/progenitor cells, respectively) by performing linear and non-linear probabilistic PCA. Taking the censoring into account results in a 2D representation of the data, which better reflects its known structure: in both datasets, our new approach results in a better separation of known cell types and is able to reveal subpopulations in one dataset that could not be resolved using standard PCA. The implementation was based on the existing Gaussian process latent variable model toolbox (https://github.com/SheffieldML/GPmat); extensions for noise models and kernels accounting for censoring are available at http://icb.helmholtz-muenchen.de/censgplvm. © The Author 2014. Published by Oxford University Press. All rights reserved.

Probabilistic PCA of censored data: accounting for uncertainties in the visualization of high-throughput single-cell qPCR data

PubMed Central

Buettner, Florian; Moignard, Victoria; Göttgens, Berthold; Theis, Fabian J.

2014-01-01

Motivation: High-throughput single-cell quantitative real-time polymerase chain reaction (qPCR) is a promising technique allowing for new insights in complex cellular processes. However, the PCR reaction can be detected only up to a certain detection limit, whereas failed reactions could be due to low or absent expression, and the true expression level is unknown. Because this censoring can occur for high proportions of the data, it is one of the main challenges when dealing with single-cell qPCR data. Principal component analysis (PCA) is an important tool for visualizing the structure of high-dimensional data as well as for identifying subpopulations of cells. However, to date it is not clear how to perform a PCA of censored data. We present a probabilistic approach that accounts for the censoring and evaluate it for two typical datasets containing single-cell qPCR data. Results: We use the Gaussian process latent variable model framework to account for censoring by introducing an appropriate noise model and allowing a different kernel for each dimension. We evaluate this new approach for two typical qPCR datasets (of mouse embryonic stem cells and blood stem/progenitor cells, respectively) by performing linear and non-linear probabilistic PCA. Taking the censoring into account results in a 2D representation of the data, which better reflects its known structure: in both datasets, our new approach results in a better separation of known cell types and is able to reveal subpopulations in one dataset that could not be resolved using standard PCA. Availability and implementation: The implementation was based on the existing Gaussian process latent variable model toolbox (https://github.com/SheffieldML/GPmat); extensions for noise models and kernels accounting for censoring are available at http://icb.helmholtz-muenchen.de/censgplvm. Contact: fbuettner.phys@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24618470

A reversible Renilla luciferase protein complementation assay for rapid identification of protein-protein interactions reveals the existence of an interaction network involved in xyloglucan biosynthesis in the plant Golgi apparatus.

PubMed

Lund, Christian H; Bromley, Jennifer R; Stenbæk, Anne; Rasmussen, Randi E; Scheller, Henrik V; Sakuragi, Yumiko

2015-01-01

A growing body of evidence suggests that protein-protein interactions (PPIs) occur amongst glycosyltransferases (GTs) required for plant glycan biosynthesis (e.g. cell wall polysaccharides and N-glycans) in the Golgi apparatus, and may control the functions of these enzymes. However, identification of PPIs in the endomembrane system in a relatively fast and simple fashion is technically challenging, hampering the progress in understanding the functional coordination of the enzymes in Golgi glycan biosynthesis. To solve the challenges, we adapted and streamlined a reversible Renilla luciferase protein complementation assay (Rluc-PCA), originally reported for use in human cells, for transient expression in Nicotiana benthamiana. We tested Rluc-PCA and successfully identified luminescence complementation amongst Golgi-localizing GTs known to form a heterodimer (GAUT1 and GAUT7) and those which homooligomerize (ARAD1). In contrast, no interaction was shown between negative controls (e.g. GAUT7, ARAD1, IRX9). Rluc-PCA was used to investigate PPIs amongst Golgi-localizing GTs involved in biosynthesis of hemicelluloses. Although no PPI was identified among six GTs involved in xylan biosynthesis, Rluc-PCA confirmed three previously proposed interactions and identified seven novel PPIs amongst GTs involved in xyloglucan biosynthesis. Notably, three of the novel PPIs were confirmed by a yeast-based split-ubiquitin assay. Finally, Gateway-enabled expression vectors were generated, allowing rapid construction of fusion proteins to the Rluc reporters and epitope tags. Our results show that Rluc-PCA coupled with transient expression in N. benthamiana is a fast and versatile method suitable for analysis of PPIs between Golgi resident proteins in an easy and mid-throughput fashion in planta. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Assessment of bioaccumulation and neurotoxicity in rats with portacaval anastomosis and exposed to manganese phosphate: a pilot study.

PubMed

Salehi, F; Carrier, G; Normandin, L; Kennedy, G; Butterworth, R F; Hazell, A; Therrien, G; Mergler, D; Philippe, S; Zayed, J

2001-12-01

The use of the additive methylcyclopentadienyl manganese tricarbonyl in unleaded gasoline has resulted in increased attention to the potential toxic effects of manganese (Mn). Hypothetically, people with chronic liver disease may be more sensitive to the adverse neurotoxic effects of Mn. In this work, bioaccumulation of Mn, as well as histopathology and neurobehavioral damage, in end-to-side portacaval anastomosis (PCA) rats exposed to Mn phosphate via inhalation was investigated. During the week before the PCA operation, 4 wk after the PCA operation, and at the end of exposure, the rats were subjected to a locomotor evaluation (day-night activities) using a computerized autotrack system. Then a group of 6 PCA rats (EXP) was exposed to 3050 microg m(-3) (Mn phosphate) for 8 h/day, 5 days/wk for 4 consecutive weeks and compared to a control group (CON), 7 PCA rats exposed to 0.03 microg m(-3). After exposure, the rats were euthanized and Mn content in tissues and organs was determined by neutron activation analysis. The manganese concentrations in blood (0.05 microg/g vs. 0.02 microg/g), lung (1.32 microg/g vs. 0.24 microg/g), cerebellum (0.85 microg/g vs. 0.64 microg/g), frontal cortex (0.87 microg/g vs. 0.61 microg/g), and globus pallidus (3.56 microg/g vs. 1.33 microg/g) were significantly higher in the exposed group compared to the control group (p <.05). No difference was observed in liver, kidney, testes, and caudate putamen between the two groups. Neuronal cell loss was assessed by neuronal cell counts. The loss of cells in globus pallidus and caudate putamen as well as in frontal cortex was significantly higher (p <.05) for the EXP group. Assessment of the locomotor activities did not reveal any significant difference. This study constitutes a first step toward our understanding of the potential adverse effects of Mn in sensitive populations.

DCE-MRI of the prostate using shutter-speed vs. Tofts model for tumor characterization and assessment of aggressiveness.

PubMed

Hectors, Stefanie J; Besa, Cecilia; Wagner, Mathilde; Jajamovich, Guido H; Haines, George K; Lewis, Sara; Tewari, Ashutosh; Rastinehad, Ardeshir; Huang, Wei; Taouli, Bachir

2017-09-01

To quantify Tofts model (TM) and shutter-speed model (SSM) perfusion parameters in prostate cancer (PCa) and noncancerous peripheral zone (PZ) and to compare the diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to Prostate Imaging and Reporting and Data System (PI-RADS) classification for the assessment of PCa aggressiveness. Fifty PCa patients (mean age 60 years old) who underwent MRI at 3.0T followed by prostatectomy were included in this Institutional Review Board-approved retrospective study. DCE-MRI parameters (K trans , v e , k ep [TM&SSM] and intracellular water molecule lifetime τ i [SSM]) were determined in PCa and PZ. Differences in DCE-MRI parameters between PCa and PZ, and between models were assessed using Wilcoxon signed-rank tests. Receiver operating characteristic (ROC) analysis for differentiation between PCa and PZ was performed for individual and combined DCE-MRI parameters. Diagnostic performance of DCE-MRI parameters for identification of aggressive PCa (Gleason ≥8, grade group [GG] ≥3 or pathology stage pT3) was assessed using ROC analysis and compared with PI-RADSv2 scores. DCE-MRI parameters were significantly different between TM and SSM and between PZ and PCa (P < 0.037). Diagnostic performances of TM and SSM for differentiation of PCa from PZ were similar (highest AUC TM: K trans +k ep 0.76, SSM: τ i +k ep 0.80). PI-RADS outperformed TM and SSM DCE-MRI for identification of Gleason ≥8 lesions (AUC PI-RADS: 0.91, highest AUC DCE-MRI: K trans +τ i SSM 0.61, P = 0.002). The diagnostic performance of PI-RADS and DCE-MRI for identification of GG ≥3 and pT3 PCa was not significantly different (P > 0.213). SSM DCE-MRI did not increase the diagnostic performance of DCE-MRI for PCa characterization. PI-RADS outperformed both TM and SSM DCE-MRI for identification of aggressive cancer. 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:837-849. © 2017 International Society for Magnetic Resonance in Medicine.

Tumor volume in insignificant prostate cancer: increasing threshold gains increasing risk.

PubMed

Schiffmann, Jonas; Connan, Judith; Salomon, Georg; Boehm, Katharina; Beyer, Burkhard; Schlomm, Thorsten; Tennstedt, Pierre; Sauter, Guido; Karakiewicz, Pierre I; Graefen, Markus; Huland, Hartwig

2015-01-01

An increased tumor volume threshold (<2.5 ml) is suggested to define insignificant prostate cancer (iPCa). We hypothesize that an increasing tumor volume within iPCa patients increases the risk of biochemical recurrence (BCR) after radical prostatectomy (RP). We relied on RP patients treated between 1992 and 2008. Multivariable Cox regression analyses predicting BCR within patients harboring favorable pathological characteristics (≤pT2, pN0/Nx, Gleason 3 + 3). Kaplan-Meier analysis was performed for BCR-free survival within iPCa patients (≤pT2, pN0/Nx, Gleason 3 + 3, tumor volume: <0.5 vs. 0.5-2.49 ml). From 1,829 patients, 141 (7.7%) and 310 (16.9%) harbored iPCa (tumor volume: <0.5 vs. 0.5-2.49 ml), respectively. Of those, 21 (14.9%) versus 31 (10.0%) had PSA >10 ng/ml. Tumor volume achieved independent predictor status for BCR. Specifically, iPCa patients with increasing tumor volume (0.5-2.49 ml) were at higher risk of BCR after RP than those with tumor volume <0.5 ml (HR: 8.8, 95% CI: 1.2-65.9, P = 0.04). Kaplan-Meier analysis recorded superior BCR-free survival in iPCa patients with lower tumor volume (<0.5 ml) (log-rank P = 0.009). The 10-year cancer-specific death rate was 0 versus 0.5%. Contemporary iPCa definition incorporates intermediate and high-risk patients (PSA: 10-20 and >20 ng/ml). Despite most favorable pathological characteristics, iPCa patients are not devoid of BCR after RP. Moreover, iPCa patients were at higher risk of BCR, when increasing tumor volume up to 2.49 ml was at play. Taken together the contemporary concept of iPCa is suboptimal. Especially, an increased tumor volume threshold for defining iPCa cannot be recommended according to our data. Clinicians might take these considerations into account during decision-making process. © 2014 Wiley Periodicals, Inc.

Antagonistic Activity and Mode of Action of Phenazine-1-Carboxylic Acid, Produced by Marine Bacterium Pseudomonas aeruginosa PA31x, Against Vibrio anguillarum In vitro and in a Zebrafish In vivo Model

PubMed Central

Zhang, Linlin; Tian, Xueying; Kuang, Shan; Liu, Ge; Zhang, Chengsheng; Sun, Chaomin

2017-01-01

Phenazine and its derivatives are very important secondary metabolites produced from Pseudomonas spp. and have exhibited broad-spectrum antifungal and antibacterial activities. However, till date, there are few reports about marine derived Pseudomonas and its production of phenazine metabolites. In this study, we isolated a marine Pseudomonas aeruginosa strain PA31x which produced natural product inhibiting the growth of Vibrio anguillarum C312, one of the most serious bacterial pathogens in marine aquaculture. Combining high-resolution electro-spray-ionization mass spectroscopy and nuclear magnetic resonance spectroscopy analyses, the functional compound against V. anguillarum was demonstrated to be phenazine-1-carboxylic acid (PCA), an important phenazine derivative. Molecular studies indicated that the production of PCA by P. aeruginosa PA31x was determined by gene clusters phz1 and phz2 in its genome. Electron microscopic results showed that treatment of V. anguillarum with PCA developed complete lysis of bacterial cells with fragmented cytoplasm being released to the surrounding environment. Additional evidence indicated that reactive oxygen species generation preceded PCA-induced microbe and cancer cell death. Notably, treatment with PCA gave highly significant protective activities against the development of V. anguillarum C312 on zebrafish. Additionally, the marine derived PCA was further found to effectively inhibit the growth of agricultural pathogens, Acidovorax citrulli NP1 and Phytophthora nicotianae JM1. Taken together, this study reveals that marine Pseudomonas derived PCA carries antagonistic activities against both aquacultural and agricultural pathogens, which broadens the application fields of PCA. PMID:28289406

Novel Imidazopyridine Derivatives Possess Anti-Tumor Effect on Human Castration-Resistant Prostate Cancer Cells

PubMed Central

Muniyan, Sakthivel; D’Cunha, Napoleon; Robinson, Tashika; Hoelting, Kyle; Dwyer, Jennifer G.; Bu, Xiu R.; Batra, Surinder K.; Lin, Ming-Fong

2015-01-01

Prostate cancer (PCa) is the second leading cause of cancer-related death afflicting United States males. Most treatments to-date for metastatic PCa include androgen-deprivation therapy and second-generation anti-androgens such as abiraterone acetate and enzalutamide. However, a majority of patients eventually develop resistance to these therapies and relapse into the lethal, castration-resistant form of PCa to which no adequate treatment option remains. Hence, there is an immediate need to develop effective therapeutic agents toward this patient population. Imidazopyridines have recently been shown to possess Akt kinase inhibitory activity; thus in this study, we investigated the inhibitory effect of novel imidazopyridine derivatives HIMP, M-MeI, OMP, and EtOP on different human castration-resistant PCa cells. Among these compounds, HIMP and M-MeI were found to possess selective dose- and time-dependent growth inhibition: they reduced castration-resistant PCa cell proliferation and spared benign prostate epithelial cells. Using LNCaP C-81 cells as the model system, these compounds also reduced colony formation as well as cell adhesion and migration, and M-MeI was the most potent in all studies. Further investigation revealed that while HIMP primarily inhibits PCa cell growth via suppression of PI3K/Akt signaling pathway, M-MeI can inhibit both PI3K/Akt and androgen receptor pathways and arrest cell growth in the G2 phase. Thus, our results indicate the novel compound M-MeI to be a promising candidate for castration-resistant PCa therapy, and future studies investigating the mechanism of imidazopyridine inhibition may aid to the development of effective anti-PCa agents. PMID:26121643

Novel Imidazopyridine Derivatives Possess Anti-Tumor Effect on Human Castration-Resistant Prostate Cancer Cells.

PubMed

Ingersoll, Matthew A; Lyons, Anastesia S; Muniyan, Sakthivel; D'Cunha, Napoleon; Robinson, Tashika; Hoelting, Kyle; Dwyer, Jennifer G; Bu, Xiu R; Batra, Surinder K; Lin, Ming-Fong

2015-01-01

Prostate cancer (PCa) is the second leading cause of cancer-related death afflicting United States males. Most treatments to-date for metastatic PCa include androgen-deprivation therapy and second-generation anti-androgens such as abiraterone acetate and enzalutamide. However, a majority of patients eventually develop resistance to these therapies and relapse into the lethal, castration-resistant form of PCa to which no adequate treatment option remains. Hence, there is an immediate need to develop effective therapeutic agents toward this patient population. Imidazopyridines have recently been shown to possess Akt kinase inhibitory activity; thus in this study, we investigated the inhibitory effect of novel imidazopyridine derivatives HIMP, M-MeI, OMP, and EtOP on different human castration-resistant PCa cells. Among these compounds, HIMP and M-MeI were found to possess selective dose- and time-dependent growth inhibition: they reduced castration-resistant PCa cell proliferation and spared benign prostate epithelial cells. Using LNCaP C-81 cells as the model system, these compounds also reduced colony formation as well as cell adhesion and migration, and M-MeI was the most potent in all studies. Further investigation revealed that while HIMP primarily inhibits PCa cell growth via suppression of PI3K/Akt signaling pathway, M-MeI can inhibit both PI3K/Akt and androgen receptor pathways and arrest cell growth in the G2 phase. Thus, our results indicate the novel compound M-MeI to be a promising candidate for castration-resistant PCa therapy, and future studies investigating the mechanism of imidazopyridine inhibition may aid to the development of effective anti-PCa agents.

Osteoblast-secreted WISP-1 promotes adherence of prostate cancer cells to bone via the VCAM-1/integrin α4β1 system.

PubMed

Chang, An-Chen; Chen, Po-Chun; Lin, Yu-Feng; Su, Chen-Ming; Liu, Ju-Fang; Lin, Tien-Huang; Chuang, Show-Mei; Tang, Chih-Hsin

2018-07-10

Bone metastasis is a frequent occurrence in prostate cancer (PCa) that is associated with severe complications such as fracture, bone pain and hypercalcemia. The cross-talk between metastatic cancer cells and bone is critical to the development and progression of bone metastases. In our previous data, we have described how the involvement of the Wnt-induced secreted protein-1/vascular cell adhesion molecule-1 (WISP-1/VCAM-1) system in this tumor-bone interaction contributes to human PCa cell motility. In this study, we found that WISP-1 regulates bone mineralization by inducing bone morphogenetic protein-2 (BMP2), BMP4 and osteopontin (OPN) expression in osteoblasts. We also found that WISP-1 inhibited RANKL-dependent osteoclastogenesis. Moreover, osteoblast-derived WISP-1 enhanced VCAM-1 expression in PCa cells and subsequently promoted the adherence of cancer cells to osteoblasts. Furthermore, endothelin-1 (ET-1) expression in PCa cells was regulated by osteoblast-derived WISP-1, which promoted integrin α4β1 expression in osteoblasts via the MAPK pathway. Pretreatment of PCa cells with VCAM-1 antibody or osteoblasts with integrin α4β1 antibody attenuated the adherence of PCa cells to osteoblasts, suggesting that integrin α4β1 serves as a ligand that captures VCAM-1 + metastatic tumor cells adhering to osteoblasts. Our findings reveal that osteoblast-derived WISP-1 plays a key role in regulating the adhesion of PCa cells to osteoblasts via the VCAM-1/integrin α4β1 system. Osteoblast-derived WISP-1 is a promising target for the prevention and inhibition of PCa-bone interaction. Copyright © 2018 Elsevier B.V. All rights reserved.

Reduced TH expression and α-synuclein accumulation contribute towards nigrostriatal dysfunction in experimental hepatic encephalopathy.

PubMed

Suárez, Isabel; Bodega, Guillermo; Rubio, Miguel; Fernández, Benjamín

2017-01-01

The present work examines α-synuclein expression in the nigrostriatal system of a rat chronic hepatic encephalopathy model induced by portacaval anastomosis (PCA). There is evidence that dopaminergic dysfunction in disease conditions is strongly associated with such expression. Possible relationships among dopaminergic neurons, astroglial cells and α-synuclein expression were sought. Brain tissue samples from rats at 1 and 6 months post-PCA, and controls, were analysed immunohistochemically using antibodies against tyrosine hydroxylase (TH), α-synuclein, glial fibrillary acidic protein (GFAP) and ubiquitin (Ub). In the control rats, TH immunoreactivity was detected in the neuronal cell bodies and processes in the substantia nigra pars compacta (SNc). A dense TH-positive network of neurons was also seen in the striatum. In the PCA-exposed rats, however, a reduction in TH-positive neurons was seen at both 1 and 6 months in the SNc, as well as a reduction in TH-positive fibres in the striatum. This was coincident with the appearance of α-synuclein-immunoreactive neurons in the SNc; some of the TH-positive neurons also showed α-synuclein immunoreactivity. In addition, α-synuclein accumulation was seen in the SNc and striatum at both 1 and 6 months post-PCA, whereas α-synuclein was only mildly expressed in the nigrostriatal pathway of the controls. Astrogliosis was also seen following PCA, as revealed by increased GFAP expression from 1 month to 6 months post-PCA in both the SN and striatum. The astroglial activation level in the SN paralleled the reduced neuronal expression of TH throughout PCA exposure. α-synuclein accumulation following PCA may induce dopaminergic dysfunction via the downregulation of TH, as well as astroglial activation.

Prostate-specific membrane antigen targeted imaging and therapy of prostate cancer using a PSMA inhibitor as a homing ligand.

PubMed

Kularatne, Sumith A; Wang, Kevin; Santhapuram, Hari-Krishna R; Low, Philip S

2009-01-01

Prostate cancer (PCa) is a major cause of mortality and morbidity in Western society today. Current methods for detecting PCa are limited, leaving most early malignancies undiagnosed and sites of metastasis in advanced disease undetected. Major deficiencies also exist in the treatment of PCa, especially metastatic disease. In an effort to improve both detection and therapy of PCa, we have developed a PSMA-targeted ligand that delivers attached imaging and therapeutic agents selectively to PCa cells without targeting normal cells. The PSMA-targeted radioimaging agent (DUPA-(99m)Tc) was found to bind PSMA-positive human PCa cells (LNCaP cell line) with nanomolar affinity (K(D) = 14 nM). Imaging and biodistribution studies revealed that DUPA-(99m)Tc localizes primarily to LNCaP cell tumor xenografts in nu/nu mice (% injected dose/gram = 11.3 at 4 h postinjection; tumor-to-muscle ratio = 75:1). Two PSMA-targeted optical imaging agents (DUPA-FITC and DUPA-rhodamine B) were also shown to efficiently label PCa cells and to internalize and traffic to intracellular endosomes. A PSMA-targeted chemotherapeutic agent (DUPA-TubH) was demonstrated to kill PSMA-positive LNCaP cells in culture (IC(50) = 3 nM) and to eliminate established tumor xenografts in nu/nu mice with no detectable weight loss. Blockade of tumor targeting upon administration of excess PSMA inhibitor (PMPA) and the absence of targeting to PSMA-negative tumors confirmed the specificity of each of the above targeted reagents for PSMA. Tandem use of the imaging and therapeutic agents targeted to the same receptor could allow detection, staging, monitoring, and treatment of PCa with improved accuracy and efficacy.

Picture agnosia as a characteristic of posterior cortical atrophy.

PubMed

Sugimoto, Azusa; Midorikawa, Akira; Koyama, Shinichi; Futamura, Akinori; Hieda, Sotaro; Kawamura, Mitsuru

2012-01-01

Posterior cortical atrophy (PCA) is a degenerative disease characterized by progressive visual agnosia with posterior cerebral atrophy. We examine the role of the picture naming test and make a number of suggestions with regard to diagnosing PCA as atypical dementia. We investigated 3 cases of early-stage PCA with 7 control cases of Alzheimer disease (AD). The patients and controls underwent a naming test with real objects and colored photographs of familiar objects. We then compared rates of correct answers. Patients with early-stage PCA showed significant inability to recognize photographs compared to real objects (F = 196.284, p = 0.0000) as measured by analysis of variants. This difficulty was also significant to AD controls (F = 58.717, p = 0.0000). Picture agnosia is a characteristic symptom of early-stage PCA, and the picture naming test is useful for the diagnosis of PCA as atypical dementia at an early stage. Copyright © 2012 S. Karger AG, Basel.

In-vitro and in-vivo evaluation of taste-masked cetirizine hydrochloride formulated in oral lyophilisates.

PubMed

Preis, Maren; Grother, Leon; Axe, Philip; Breitkreutz, Jörg

2015-08-01

The use of solid oral dosage forms is typically favored with regard to stability and ease of administration. The aim of this study was to investigate whether cyclodextrins (CD) or ion exchange resins (IER) could be used to taste-mask cetirizine HCl when formulated in a freeze-dried oral formulation. The oral lyophilisates were produced using the Zydis(®) technology that offer the opportunity to produce the dosage form directly in the aluminum laminate blister packs. This study confirmed that a pre-formed resinate of cetirizine HCl and various cyclodextrins can be successfully incorporated into the Zydis(®) oral lyophilisate. A chemically stable product with acceptable release profile was obtained in the case of cyclodextrin. This study has also demonstrated that the Insent(®) taste sensing system is a useful technique for predicting the taste-masking potential of Zydis(®) formulations. The electronic taste sensing system (e-tongue) data can be used to provide guidance on the selection of taste-masked formulations. Principal component analysis (PCA) of sensor data by plotting the PCA scores revealed the effects of used taste-masking techniques on the e-tongue sensors, indicating the successful taste improvement. The PCA plot of the taste sensor data revealed larger distances between the non-taste-masked sample and the CD- and IER-loaded samples, and the shift toward the drug-free formulations and excipient signals indicates a modification of the product taste. The human taste trial confirms the acceptability of the selected promising formulations. The taste evaluation results showed that an effectively taste-masked formulation has been achieved using β-cyclodextrin and cherry/sucralose flavor system with over 80% of volunteers finding the tablet to be acceptable. Copyright © 2015 Elsevier B.V. All rights reserved.

Principal Component Analysis of Thermographic Data

NASA Technical Reports Server (NTRS)

Winfree, William P.; Cramer, K. Elliott; Zalameda, Joseph N.; Howell, Patricia A.; Burke, Eric R.

2015-01-01

Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. While a reliable technique for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the "good" material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued where a fixed set of eigenvectors, generated from an analytic model of the thermal response of the material under examination, is used to process the thermal data from composite materials. This method has been applied for characterization of flaws.

Evaluation of skin melanoma in spectral range 450-950 nm using principal component analysis

NASA Astrophysics Data System (ADS)

Jakovels, D.; Lihacova, I.; Kuzmina, I.; Spigulis, J.

2013-06-01

Diagnostic potential of principal component analysis (PCA) of multi-spectral imaging data in the wavelength range 450- 950 nm for distant skin melanoma recognition is discussed. Processing of the measured clinical data by means of PCA resulted in clear separation between malignant melanomas and pigmented nevi.

AlleleCoder: a PERL script for coding codominant polymorphism data for PCA analysis

USDA-ARS?s Scientific Manuscript database

A useful biological interpretation of diploid heterozygotes is in terms of the dose of the common allele (0, 1 or 2 copies). We have developed a PERL script that converts FASTA files into coded spreadsheets suitable for Principal Component Analysis (PCA). In combination with R and R Commander, two- ...

Principle Component Analysis with Incomplete Data: A simulation of R pcaMethods package in Constructing an Environmental Quality Index with Missing Data

EPA Science Inventory

Missing data is a common problem in the application of statistical techniques. In principal component analysis (PCA), a technique for dimensionality reduction, incomplete data points are either discarded or imputed using interpolation methods. Such approaches are less valid when ...

Raman chemical mapping reveals site of action of HIV protease inhibitors in HPV16 E6 expressing cervical carcinoma cells.

PubMed

Kim, Dong-Hyun; Jarvis, Roger M; Allwood, J William; Batman, Gavin; Moore, Rowan E; Marsden-Edwards, Emma; Hampson, Lynne; Hampson, Ian N; Goodacre, Royston

2010-12-01

It has been shown that the HIV protease inhibitors indinavir and lopinavir may have activity against the human papilloma virus (HPV) type 16 inhibiting HPV E6-mediated proteasomal degradation of p53 in cultured cervical carcinoma cells. However, their mode and site of action is unknown. HPV-negative C33A cervical carcinoma cells and the same cells stably transfected with E6 (C33AE6) were exposed to indinavir and lopinavir at concentrations of 1 mM and 30 μM, respectively. The intracellular distribution of metabolites and metabolic changes induced by these treatments were investigated by Raman microspectroscopic imaging combined with the analysis of cell fractionation products by liquid chromatography-mass spectrometry (LC-MS). A uniform cellular distribution of proteins was found in drug-treated cells irrespective of cell type. Indinavir was observed to co-localise with nucleic acid in the nucleus, but only in E6 expressing cells. Principal components analysis (PCA) score maps generated on the full Raman hypercube and the corresponding PCA loadings plots revealed that the majority of metabolic variations influenced by the drug exposure within the cells were associated with changes in nucleic acids. Analysis of cell fractionation products by LC-MS confirmed that the level of indinavir in nuclear extracts was approximately eight-fold greater than in the cytoplasm. These data demonstrate that indinavir undergoes enhanced nuclear accumulation in E6-expressing cells, which suggests that this is the most likely site of action for this compound against HPV.

Counting or Chunking?

PubMed Central

Spotorno, Nicola; McMillan, Corey T.; Powers, John P.; Clark, Robin; Grossman, Murray

2014-01-01

A growing amount of empirical data is showing that the ability to manipulate quantities in a precise and efficient fashion is rooted in cognitive mechanisms devoted to specific aspects of numbers processing. The Analog number system (ANS) has a reasonable representation of quantities up to about 4, and represents larger quantities on the basis of a numerical ratio between quantities. In order to represent the precise cardinality of a number, the ANS may be supported by external algorithms such as language, leading to a “Precise Number System”. In the setting of limited language, other number-related systems can appear. For example the Parallel Individuation system (PIS) supports a “chunking mechanism” that clusters units of larger numerosities into smaller subsets. In the present study we investigated number processing in non-aphasic patients with Corticobasal Syndrome (CBS) and Posterior Cortical Atrophy (PCA), two neurodegenerative conditions that are associated with progressive parietal atrophy. The present study investigated these number systems in CBS and PCA by assessing the property of the ANS associated with smaller and larger numerosities, and the chunking property of the PIS. The results revealed that CBS/PCA patients are impaired in simple calculations (e.g., addition and subtraction) and that their performance strongly correlates with the size of the numbers involved in these calculations, revealing a clear magnitude effect. This magnitude effect correlated with gray matter atrophy in parietal regions. Moreover, a numeral-dots transcoding task showed that CBS/PCA patients are able to take advantage of clustering in the spatial distribution of the dots of the array. The relative advantage associated with chunking compared to a random spatial distribution correlated with both parietal and prefrontal regions. These results shed light on the properties of systems for representing number knowledge in non-aphasic patients with CBS and PCA. PMID:25278132

Population Analysis of Disabled Children by Departments in France

NASA Astrophysics Data System (ADS)

Meidatuzzahra, Diah; Kuswanto, Heri; Pech, Nicolas; Etchegaray, Amélie

2017-06-01

In this study, a statistical analysis is performed by model the variations of the disabled about 0-19 years old population among French departments. The aim is to classify the departments according to their profile determinants (socioeconomic and behavioural profiles). The analysis is focused on two types of methods: principal component analysis (PCA) and multiple correspondences factorial analysis (MCA) to review which one is the best methods for interpretation of the correlation between the determinants of disability (independent variable). The PCA is the best method for interpretation of the correlation between the determinants of disability (independent variable). The PCA reduces 14 determinants of disability to 4 axes, keeps 80% of total information, and classifies them into 7 classes. The MCA reduces the determinants to 3 axes, retains only 30% of information, and classifies them into 4 classes.

Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) Significantly Improve Prostate Cancer Detection at Initial Biopsy in a Total PSA Range of 2–10 ng/ml

PubMed Central

Perdonà, Sisto; Marino, Ada; Mazzarella, Claudia; Perruolo, Giuseppe; D’Esposito, Vittoria; Cosimato, Vincenzo; Buonerba, Carlo; Di Lorenzo, Giuseppe; Musi, Gennaro; De Cobelli, Ottavio; Chun, Felix K.; Terracciano, Daniela

2013-01-01

Many efforts to reduce prostate specific antigen (PSA) overdiagnosis and overtreatment have been made. To this aim, Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) have been proposed as new more specific biomarkers. We evaluated the ability of phi and PCA3 to identify prostate cancer (PCa) at initial prostate biopsy in men with total PSA range of 2–10 ng/ml. The performance of phi and PCA3 were evaluated in 300 patients undergoing first prostate biopsy. ROC curve analyses tested the accuracy (AUC) of phi and PCA3 in predicting PCa. Decision curve analyses (DCA) were used to compare the clinical benefit of the two biomarkers. We found that the AUC value of phi (0.77) was comparable to those of %p2PSA (0.76) and PCA3 (0.73) with no significant differences in pairwise comparison (%p2PSA vs phi p = 0.673, %p2PSA vs. PCA3 p = 0.417 and phi vs. PCA3 p = 0.247). These three biomarkers significantly outperformed fPSA (AUC = 0.60), % fPSA (AUC = 0.62) and p2PSA (AUC = 0.63). At DCA, phi and PCA3 exhibited a very close net benefit profile until the threshold probability of 25%, then phi index showed higher net benefit than PCA3. Multivariable analysis showed that the addition of phi and PCA3 to the base multivariable model (age, PSA, %fPSA, DRE, prostate volume) increased predictive accuracy, whereas no model improved single biomarker performance. Finally we showed that subjects with active surveillance (AS) compatible cancer had significantly lower phi and PCA3 values (p<0.001 and p = 0.01, respectively). In conclusion, both phi and PCA3 comparably increase the accuracy in predicting the presence of PCa in total PSA range 2–10 ng/ml at initial biopsy, outperforming currently used %fPSA. PMID:23861782

Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) significantly improve prostate cancer detection at initial biopsy in a total PSA range of 2-10 ng/ml.

PubMed

Ferro, Matteo; Bruzzese, Dario; Perdonà, Sisto; Marino, Ada; Mazzarella, Claudia; Perruolo, Giuseppe; D'Esposito, Vittoria; Cosimato, Vincenzo; Buonerba, Carlo; Di Lorenzo, Giuseppe; Musi, Gennaro; De Cobelli, Ottavio; Chun, Felix K; Terracciano, Daniela

2013-01-01

Many efforts to reduce prostate specific antigen (PSA) overdiagnosis and overtreatment have been made. To this aim, Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) have been proposed as new more specific biomarkers. We evaluated the ability of phi and PCA3 to identify prostate cancer (PCa) at initial prostate biopsy in men with total PSA range of 2-10 ng/ml. The performance of phi and PCA3 were evaluated in 300 patients undergoing first prostate biopsy. ROC curve analyses tested the accuracy (AUC) of phi and PCA3 in predicting PCa. Decision curve analyses (DCA) were used to compare the clinical benefit of the two biomarkers. We found that the AUC value of phi (0.77) was comparable to those of %p2PSA (0.76) and PCA3 (0.73) with no significant differences in pairwise comparison (%p2PSA vs phi p = 0.673, %p2PSA vs. PCA3 p = 0.417 and phi vs. PCA3 p = 0.247). These three biomarkers significantly outperformed fPSA (AUC = 0.60), % fPSA (AUC = 0.62) and p2PSA (AUC = 0.63). At DCA, phi and PCA3 exhibited a very close net benefit profile until the threshold probability of 25%, then phi index showed higher net benefit than PCA3. Multivariable analysis showed that the addition of phi and PCA3 to the base multivariable model (age, PSA, %fPSA, DRE, prostate volume) increased predictive accuracy, whereas no model improved single biomarker performance. Finally we showed that subjects with active surveillance (AS) compatible cancer had significantly lower phi and PCA3 values (p<0.001 and p = 0.01, respectively). In conclusion, both phi and PCA3 comparably increase the accuracy in predicting the presence of PCa in total PSA range 2-10 ng/ml at initial biopsy, outperforming currently used %fPSA.

A Seven-Gene Locus for Synthesis of Phenazine-1-Carboxylic Acid by Pseudomonas fluorescens 2-79

PubMed Central

Mavrodi, Dmitri V.; Ksenzenko, Vladimir N.; Bonsall, Robert F.; Cook, R. James; Boronin, Alexander M.; Thomashow, Linda S.

1998-01-01

Pseudomonas fluorescens 2-79 produces the broad-spectrum antibiotic phenazine-1-carboxylic acid (PCA), which is active against a variety of fungal root pathogens. In this study, seven genes designated phzABCDEFG that are sufficient for synthesis of PCA were localized within a 6.8-kb BglII-XbaI fragment from the phenazine biosynthesis locus of strain 2-79. Polypeptides corresponding to all phz genes were identified by analysis of recombinant plasmids in a T7 promoter/polymerase expression system. Products of the phzC, phzD, and phzE genes have similarities to enzymes of shikimic acid and chorismic acid metabolism and, together with PhzF, are absolutely necessary for PCA production. PhzG is similar to pyridoxamine-5′-phosphate oxidases and probably is a source of cofactor for the PCA-synthesizing enzyme(s). Products of the phzA and phzB genes are highly homologous to each other and may be involved in stabilization of a putative PCA-synthesizing multienzyme complex. Two new genes, phzX and phzY, that are homologous to phzA and phzB, respectively, were cloned and sequenced from P. aureofaciens 30-84, which produces PCA, 2-hydroxyphenazine-1-carboxylic acid, and 2-hydroxyphenazine. Based on functional analysis of the phz genes from strains 2-79 and 30-84, we postulate that different species of fluorescent pseudomonads have similar genetic systems that confer the ability to synthesize PCA. PMID:9573209

IMPROVED SEARCH OF PRINCIPAL COMPONENT ANALYSIS DATABASES FOR SPECTRO-POLARIMETRIC INVERSION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Casini, R.; Lites, B. W.; Ramos, A. Asensio

2013-08-20

We describe a simple technique for the acceleration of spectro-polarimetric inversions based on principal component analysis (PCA) of Stokes profiles. This technique involves the indexing of the database models based on the sign of the projections (PCA coefficients) of the first few relevant orders of principal components of the four Stokes parameters. In this way, each model in the database can be attributed a distinctive binary number of 2{sup 4n} bits, where n is the number of PCA orders used for the indexing. Each of these binary numbers (indices) identifies a group of ''compatible'' models for the inversion of amore » given set of observed Stokes profiles sharing the same index. The complete set of the binary numbers so constructed evidently determines a partition of the database. The search of the database for the PCA inversion of spectro-polarimetric data can profit greatly from this indexing. In practical cases it becomes possible to approach the ideal acceleration factor of 2{sup 4n} as compared to the systematic search of a non-indexed database for a traditional PCA inversion. This indexing method relies on the existence of a physical meaning in the sign of the PCA coefficients of a model. For this reason, the presence of model ambiguities and of spectro-polarimetric noise in the observations limits in practice the number n of relevant PCA orders that can be used for the indexing.« less

Facilitating Neuronal Connectivity Analysis of Evoked Responses by Exposing Local Activity with Principal Component Analysis Preprocessing: Simulation of Evoked MEG

PubMed Central

Gao, Lin; Zhang, Tongsheng; Wang, Jue; Stephen, Julia

2014-01-01

When connectivity analysis is carried out for event related EEG and MEG, the presence of strong spatial correlations from spontaneous activity in background may mask the local neuronal evoked activity and lead to spurious connections. In this paper, we hypothesized PCA decomposition could be used to diminish the background activity and further improve the performance of connectivity analysis in event related experiments. The idea was tested using simulation, where we found that for the 306-channel Elekta Neuromag system, the first 4 PCs represent the dominant background activity, and the source connectivity pattern after preprocessing is consistent with the true connectivity pattern designed in the simulation. Improving signal to noise of the evoked responses by discarding the first few PCs demonstrates increased coherences at major physiological frequency bands when removing the first few PCs. Furthermore, the evoked information was maintained after PCA preprocessing. In conclusion, it is demonstrated that the first few PCs represent background activity, and PCA decomposition can be employed to remove it to expose the evoked activity for the channels under investigation. Therefore, PCA can be applied as a preprocessing approach to improve neuronal connectivity analysis for event related data. PMID:22918837

Facilitating neuronal connectivity analysis of evoked responses by exposing local activity with principal component analysis preprocessing: simulation of evoked MEG.

PubMed

Gao, Lin; Zhang, Tongsheng; Wang, Jue; Stephen, Julia

2013-04-01

When connectivity analysis is carried out for event related EEG and MEG, the presence of strong spatial correlations from spontaneous activity in background may mask the local neuronal evoked activity and lead to spurious connections. In this paper, we hypothesized PCA decomposition could be used to diminish the background activity and further improve the performance of connectivity analysis in event related experiments. The idea was tested using simulation, where we found that for the 306-channel Elekta Neuromag system, the first 4 PCs represent the dominant background activity, and the source connectivity pattern after preprocessing is consistent with the true connectivity pattern designed in the simulation. Improving signal to noise of the evoked responses by discarding the first few PCs demonstrates increased coherences at major physiological frequency bands when removing the first few PCs. Furthermore, the evoked information was maintained after PCA preprocessing. In conclusion, it is demonstrated that the first few PCs represent background activity, and PCA decomposition can be employed to remove it to expose the evoked activity for the channels under investigation. Therefore, PCA can be applied as a preprocessing approach to improve neuronal connectivity analysis for event related data.

An Intelligent Architecture Based on Field Programmable Gate Arrays Designed to Detect Moving Objects by Using Principal Component Analysis

PubMed Central

Bravo, Ignacio; Mazo, Manuel; Lázaro, José L.; Gardel, Alfredo; Jiménez, Pedro; Pizarro, Daniel

2010-01-01

This paper presents a complete implementation of the Principal Component Analysis (PCA) algorithm in Field Programmable Gate Array (FPGA) devices applied to high rate background segmentation of images. The classical sequential execution of different parts of the PCA algorithm has been parallelized. This parallelization has led to the specific development and implementation in hardware of the different stages of PCA, such as computation of the correlation matrix, matrix diagonalization using the Jacobi method and subspace projections of images. On the application side, the paper presents a motion detection algorithm, also entirely implemented on the FPGA, and based on the developed PCA core. This consists of dynamically thresholding the differences between the input image and the one obtained by expressing the input image using the PCA linear subspace previously obtained as a background model. The proposal achieves a high ratio of processed images (up to 120 frames per second) and high quality segmentation results, with a completely embedded and reliable hardware architecture based on commercial CMOS sensors and FPGA devices. PMID:22163406

An intelligent architecture based on Field Programmable Gate Arrays designed to detect moving objects by using Principal Component Analysis.

PubMed

Bravo, Ignacio; Mazo, Manuel; Lázaro, José L; Gardel, Alfredo; Jiménez, Pedro; Pizarro, Daniel

2010-01-01

This paper presents a complete implementation of the Principal Component Analysis (PCA) algorithm in Field Programmable Gate Array (FPGA) devices applied to high rate background segmentation of images. The classical sequential execution of different parts of the PCA algorithm has been parallelized. This parallelization has led to the specific development and implementation in hardware of the different stages of PCA, such as computation of the correlation matrix, matrix diagonalization using the Jacobi method and subspace projections of images. On the application side, the paper presents a motion detection algorithm, also entirely implemented on the FPGA, and based on the developed PCA core. This consists of dynamically thresholding the differences between the input image and the one obtained by expressing the input image using the PCA linear subspace previously obtained as a background model. The proposal achieves a high ratio of processed images (up to 120 frames per second) and high quality segmentation results, with a completely embedded and reliable hardware architecture based on commercial CMOS sensors and FPGA devices.

Association between age-related reductions in testosterone and risk of prostate cancer-An analysis of patients' data with prostatic diseases.

PubMed

Wang, Kai; Chen, Xinguang; Bird, Victoria Y; Gerke, Travis A; Manini, Todd M; Prosperi, Mattia

2017-11-01

The relationship between serum total testosterone and prostate cancer (PCa) risk is controversial. The hypothesis that faster age-related reduction in testosterone is linked with increased PCa risk remains untested. We conducted our study at a tertiary-level hospital in southeast of the USA, and derived data from the Medical Registry Database of individuals that were diagnosed of any prostate-related disease from 2001 to 2015. Cases were those diagnosed of PCa and had one or more measurements of testosterone prior to PCa diagnosis. Controls were those without PCa and had one or more testosterone measurements. Multivariable logistic regression models for PCa risk of absolute levels (one-time measure and 5-year average) and annual change in testosterone were respectively constructed. Among a total of 1,559 patients, 217 were PCa cases, and neither one-time measure nor 5-year average of testosterone was found to be significantly associated with PCa risk. Among the 379 patients with two or more testosterone measurements, 27 were PCa cases. For every 10 ng/dL increment in annual reduction of testosterone, the risk of PCa would increase by 14% [adjusted odds ratio, 1.14; 95% confidence interval (CI), 1.03-1.25]. Compared to patients with a relatively stable testosterone, patients with an annual testosterone reduction of more than 30 ng/dL had 5.03 [95% CI: 1.53, 16.55] fold increase in PCa risk. This implies a faster age-related reduction in, but not absolute level of serum total testosterone as a risk factor for PCa. Further longitudinal studies are needed to confirm this finding. © 2017 UICC.

An electrophysiological index of changes in risk decision-making strategies.

PubMed

Zhang, Dandan; Gu, Ruolei; Wu, Tingting; Broster, Lucas S; Luo, Yi; Jiang, Yang; Luo, Yue-jia

2013-07-01

Human decision-making is significantly modulated by previously experienced outcomes. Using event-related potentials (ERPs), we examined whether ERP components evoked by outcome feedbacks could serve as biomarkers to signal the influence of current outcome evaluation on subsequent decision-making. In this study, 18 adult volunteers participated in a simple monetary gambling task, in which they were asked to choose between two options that differed in risk. Their decisions were immediately followed by outcome presentation. Temporospatial principle component analysis (PCA) was applied to the outcome-onset locked ERPs in the 200-1000 ms time window. The PCA factors that approximated classical ERP components (P2, feedback-related negativity, P3a, and P3b) in terms of time course and scalp distribution were tested for their association with subsequent decision-making strategies. Our results revealed that a fronto-central PCA factor approximating the classical P3a was related to changes of decision-making strategies on subsequent trials. The decision to switch between high- and low-risk options resulted in a larger P3a relative to the decision to retain the same choice. According to the results, we suggest that the amplitude of the fronto-central P3a is an electrophysiological index of the influence of current outcome on subsequent risk decision-making. Furthermore, the ERP source analysis indicated that the activations of the frontopolar cortex and sensorimotor cortex were involved in subsequent changes of strategies, which enriches our understanding of the neural mechanisms of adjusting decision-making strategies based on previous experience. Copyright © 2013 Elsevier Ltd. All rights reserved.

Decreased number of mast cells infiltrating into needle biopsy specimens leads to a better prognosis of prostate cancer

PubMed Central

Nonomura, N; Takayama, H; Nishimura, K; Oka, D; Nakai, Y; Shiba, M; Tsujimura, A; Nakayama, M; Aozasa, K; Okuyama, A

2007-01-01

Mast cell infiltration is often observed around human tumours. Inflammatory cells such as macrophages, neutrophils and mast cells infiltrating around tumours are known to contribute to tumour growth; however, the clinical significance of mast cell invasion in prostate cancer (PCa) has not been investigated. Mast cell infiltration was evaluated in 104 patients (age range, 45–88 years; median, 72 years), who underwent needle biopsy of the prostate and were confirmed to have PCa. Needle biopsy specimens of prostate were sliced into 5-μm-thick sections and immunostained for mast cells with monoclonal antibody against mast cell-specific tryptase. Mast cells were counted systematically under a microscope (× 400 magnification), and the relations between mast cell numbers and clinicopathologic findings were evaluated. The mast cell count was evaluated for prognostic value by multivariate analysis. Mast cells were immunostained around the cancer foci. The median number of mast cells in each case was 16. The mast cell count was higher around cancer foci in patients with higher Gleason scores than in those with low Gleason scores. The mast cell number correlated well with clinical stage (P<0.001). Prostate-specific antigen-free survival of patients with higher mast cell counts was better than that in patients with lower mast cell counts (P<0.001). Multivariate analysis revealed that mast cell count was a significant prognostic factor (P<0.005). The number of mast cells infiltrating around cancer foci in prostate biopsy specimens can be a significant prognostic factor of PCa. PMID:17848955

An electrophysiological index of changes in risk decision-making strategies

PubMed Central

Zhang, Dandan; Gu, Ruolei; Wu, Tingting; Broster, Lucas S.; Luo, Yi; Jiang, Yang; Luo, Yue-jia

2014-01-01

Human decision-making is significantly modulated by previously experienced outcomes. Using event-related potentials (ERPs), we examined whether ERP components evoked by outcome feedbacks could serve as biomarkers to signal the influence of current outcome evaluation on subsequent decision-making. In this study, eighteen adult volunteers participated in a simple monetary gambling task, in which they were asked to choose between two options that differed in risk. Their decisions were immediately followed by outcome presentation. Temporospatial principle component analysis (PCA) was applied to the outcome-onset locked ERPs in the -200 – 1000 ms time window. The PCA factors that approximated classical ERP components (P2, feedback-related negativity, P3a, & P3b) in terms of time course and scalp distribution were tested for their association with subsequent decision-making strategies. Our results revealed that a fronto-central PCA factor approximating the classical P3a was related to changes of decision-making strategies on subsequent trials. The decision to switch between high- and low-risk options resulted in a larger P3a relative to the decision to retain the same choice. According to the results, we suggest the amplitude of the fronto-central P3a is an electrophysiological index of the influence of current outcome on subsequent risk decision-making. Furthermore, the ERP source analysis indicated that the activations of the frontopolar cortex and sensorimotor cortex were involved in subsequent changes of strategies, which enriches our understanding of the neural mechanisms of adjusting decision-making strategies based on previous experience. PMID:23643796

A Systematic Review and Meta-analysis of the Diagnostic Accuracy of Prostate Health Index and 4-Kallikrein Panel Score in Predicting Overall and High-grade Prostate Cancer.

PubMed

Russo, Giorgio Ivan; Regis, Federica; Castelli, Tommaso; Favilla, Vincenzo; Privitera, Salvatore; Giardina, Raimondo; Cimino, Sebastiano; Morgia, Giuseppe

2017-08-01

Markers for prostate cancer (PCa) have progressed over recent years. In particular, the prostate health index (PHI) and the 4-kallikrein (4K) panel have been demonstrated to improve the diagnosis of PCa. We aimed to review the diagnostic accuracy of PHI and the 4K panel for PCa detection. We performed a systematic literature search of PubMed, EMBASE, Cochrane, and Academic One File databases until July 2016. We included diagnostic accuracy studies that used PHI or 4K panel for the diagnosis of PCa or high-grade PCa. The methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Twenty-eight studies including 16,762 patients have been included for the analysis. The pooled data showed a sensitivity of 0.89 and 0.74 for PHI and 4K panel, respectively, for PCa detection and a pooled specificity of 0.34 and 0.60 for PHI and 4K panel, respectively. The derived area under the curve (AUC) from the hierarchical summary receiver operating characteristic (HSROC) showed an accuracy of 0.76 and 0.72 for PHI and 4K panel respectively. For high-grade PCa detection, the pooled sensitivity was 0.93 and 0.87 for PHI and 4K panel, respectively, whereas the pooled specificity was 0.34 and 0.61 for PHI and 4K panel, respectively. The derived AUC from the HSROC showed an accuracy of 0.82 and 0.81 for PHI and 4K panel, respectively. Both PHI and the 4K panel provided good diagnostic accuracy in detecting overall and high-grade PCa. Copyright © 2016 Elsevier Inc. All rights reserved.

Urinary MicroRNAs of Prostate Cancer: Virus-Encoded hsv1-miRH18 and hsv2-miR-H9-5p Could Be Valuable Diagnostic Markers.

PubMed

Yun, Seok Joong; Jeong, Pildu; Kang, Ho Won; Kim, Ye-Hwan; Kim, Eun-Ah; Yan, Chunri; Choi, Young-Ki; Kim, Dongho; Kim, Jung Min; Kim, Seon-Kyu; Kim, Seon-Young; Kim, Sang Tae; Kim, Won Tae; Lee, Ok-Jun; Koh, Gou-Young; Moon, Sung-Kwon; Kim, Isaac Yi; Kim, Jayoung; Choi, Yung-Hyun; Kim, Wun-Jae

2015-06-01

MicroRNAs (miRNAs) in biological fluids are potential biomarkers for the diagnosis and assessment of urological diseases such as benign prostatic hyperplasia (BPH) and prostate cancer (PCa). The aim of the study was to identify and validate urinary cell-free miRNAs that can segregate patients with PCa from those with BPH. In total, 1,052 urine, 150 serum, and 150 prostate tissue samples from patients with PCa or BPH were used in the study. A urine-based miRNA microarray analysis suggested the presence of differentially expressed urinary miRNAs in patients with PCa, and these were further validated in three independent PCa cohorts, using a quantitative reverse transcriptionpolymerase chain reaction analysis. The expression levels of hsa-miR-615-3p, hsv1-miR-H18, hsv2-miR-H9-5p, and hsa-miR-4316 were significantly higher in urine samples of patients with PCa than in those of BPH controls. In particular, herpes simplex virus (hsv)-derived hsv1-miR-H18 and hsv2-miR-H9-5p showed better diagnostic performance than did the serum prostate-specific antigen (PSA) test for patients in the PSA gray zone. Furthermore, a combination of urinary hsv2-miR-H9-5p with serum PSA showed high sensitivity and specificity, providing a potential clinical benefit by reducing unnecessary biopsies. Our findings showed that hsv-encoded hsv1-miR-H18 and hsv2-miR-H9-5p are significantly associated with PCa and can facilitate early diagnosis of PCa for patients within the serum PSA gray zone.

Urinary MicroRNAs of Prostate Cancer: Virus-Encoded hsv1-miRH18 and hsv2-miR-H9-5p Could Be Valuable Diagnostic Markers

PubMed Central

Yun, Seok Joong; Jeong, Pildu; Kang, Ho Won; Kim, Ye-Hwan; Kim, Eun-Ah; Yan, Chunri; Choi, Young-Ki; Kim, Dongho; Kim, Jung Min; Kim, Seon-Kyu; Kim, Seon-Young; Kim, Sang Tae; Kim, Won Tae; Lee, Ok-Jun; Koh, Gou-Young; Moon, Sung-Kwon; Kim, Isaac Yi; Kim, Jayoung; Choi, Yung-Hyun; Kim, Wun-Jae

2015-01-01

Purpose: MicroRNAs (miRNAs) in biological fluids are potential biomarkers for the diagnosis and assessment of urological diseases such as benign prostatic hyperplasia (BPH) and prostate cancer (PCa). The aim of the study was to identify and validate urinary cell-free miRNAs that can segregate patients with PCa from those with BPH. Methods: In total, 1,052 urine, 150 serum, and 150 prostate tissue samples from patients with PCa or BPH were used in the study. A urine-based miRNA microarray analysis suggested the presence of differentially expressed urinary miRNAs in patients with PCa, and these were further validated in three independent PCa cohorts, using a quantitative reverse transcriptionpolymerase chain reaction analysis. Results: The expression levels of hsa-miR-615-3p, hsv1-miR-H18, hsv2-miR-H9-5p, and hsa-miR-4316 were significantly higher in urine samples of patients with PCa than in those of BPH controls. In particular, herpes simplex virus (hsv)-derived hsv1-miR-H18 and hsv2-miR-H9-5p showed better diagnostic performance than did the serum prostate-specific antigen (PSA) test for patients in the PSA gray zone. Furthermore, a combination of urinary hsv2-miR-H9-5p with serum PSA showed high sensitivity and specificity, providing a potential clinical benefit by reducing unnecessary biopsies. Conclusions: Our findings showed that hsv-encoded hsv1-miR-H18 and hsv2-miR-H9-5p are significantly associated with PCa and can facilitate early diagnosis of PCa for patients within the serum PSA gray zone. PMID:26126436

Blow Flies from Forest Fragments Embedded in Different Land Uses: Implications for Selecting Indicators in Forensic Entomology.

PubMed

de Souza, Mirian S; Pepinelli, Mateus; de Almeida, Eduardo C; Ochoa-Quintero, Jose M; Roque, Fabio O

2016-01-01

Given the general expectation that forest loss can alter biodiversity patterns, we hypothesize that blow fly species abundances differ in a gradient of native vegetation cover. This study was conducted in 17 fragments across different landscapes in central Brazil. Different land cover type proportions were used to represent landscape structure. In total, 2334 specimens of nine species of Calliphoridae were collected. We used principal component analysis (PCA) to reduce dimensionality and multicollinearity of the landscape data. The first component explained 70%, and it represented a gradient of forest-pasture land uses. Alien species showed a wide distribution in different fragments with no clear relationship between the abundance values and the scores of PCA axes, whereas native species occurred only in areas with a predominance of forest cover. Our study revealed that certain native species may be sensitive to forest loss at the landscape scale, and they represent a bioindicator in forensic entomology. © 2015 American Academy of Forensic Sciences.

A comparison between different coronagraphic data reduction techniques

NASA Astrophysics Data System (ADS)

Carolo, E.; Vassallo, D.; Farinato, J.; Bergomi, M.; Bonavita, M.; Carlotti, A.; D'Orazi, V.; Greggio, D.; Magrin, D.; Mesa, D.; Pinna, E.; Puglisi, A.; Stangalini, M.; Verinaud, C.; Viotto, V.

2016-07-01

A robust post processing technique is mandatory for analysing the coronagraphic high contrast imaging data. Angular Differential Imaging (ADI) and Principal Component Analysis (PCA) are the most used approaches to suppress the quasi-static structure presents in the Point Spread Function (PSF) for revealing planets at different separations from the host star. In this work, we present the comparison between ADI and PCA applied to System of coronagraphy with High order Adaptive optics from R to K band (SHARK-NIR), which will be implemented at Large Binocular Telescope (LBT). The comparison has been carried out by using as starting point the simulated wavefront residuals of the LBT Adaptive Optics (AO) system, in different observing conditions. Accurate tests for tuning the post processing parameters to obtain the best performance from each technique were performed in various seeing conditions (0:4"-1") for star magnitude ranging from 8 to 12, with particular care in finding the best compromise between quasi static speckle subtraction and planets detection.

Cannibalism Affects Core Metabolic Processes in Helicoverpa armigera Larvae-A 2D NMR Metabolomics Study.

PubMed

Vergara, Fredd; Shino, Amiu; Kikuchi, Jun

2016-09-02

Cannibalism is known in many insect species, yet its impact on insect metabolism has not been investigated in detail. This study assessed the effects of cannibalism on the metabolism of fourth-instar larvae of the non-predatory insect Helicoverpa armigera (Lepidotera: Noctuidea). Two groups of larvae were analyzed: one group fed with fourth-instar larvae of H. armigera (cannibal), the other group fed with an artificial plant diet. Water-soluble small organic compounds present in the larvae were analyzed using two-dimensional nuclear magnetic resonance (NMR) and principal component analysis (PCA). Cannibalism negatively affected larval growth. PCA of NMR spectra showed that the metabolic profiles of cannibal and herbivore larvae were statistically different with monomeric sugars, fatty acid- and amino acid-related metabolites as the most variable compounds. Quantitation of ¹H-(13)C HSQC (Heteronuclear Single Quantum Coherence) signals revealed that the concentrations of glucose, glucono-1,5-lactone, glycerol phosphate, glutamine, glycine, leucine, isoleucine, lysine, ornithine, proline, threonine and valine were higher in the herbivore larvae.

Facilitating text reading in posterior cortical atrophy.

PubMed

Yong, Keir X X; Rajdev, Kishan; Shakespeare, Timothy J; Leff, Alexander P; Crutch, Sebastian J

2015-07-28

We report (1) the quantitative investigation of text reading in posterior cortical atrophy (PCA), and (2) the effects of 2 novel software-based reading aids that result in dramatic improvements in the reading ability of patients with PCA. Reading performance, eye movements, and fixations were assessed in patients with PCA and typical Alzheimer disease and in healthy controls (experiment 1). Two reading aids (single- and double-word) were evaluated based on the notion that reducing the spatial and oculomotor demands of text reading might support reading in PCA (experiment 2). Mean reading accuracy in patients with PCA was significantly worse (57%) compared with both patients with typical Alzheimer disease (98%) and healthy controls (99%); spatial aspects of passages were the primary determinants of text reading ability in PCA. Both aids led to considerable gains in reading accuracy (PCA mean reading accuracy: single-word reading aid = 96%; individual patient improvement range: 6%-270%) and self-rated measures of reading. Data suggest a greater efficiency of fixations and eye movements under the single-word reading aid in patients with PCA. These findings demonstrate how neurologic characterization of a neurodegenerative syndrome (PCA) and detailed cognitive analysis of an important everyday skill (reading) can combine to yield aids capable of supporting important everyday functional abilities. This study provides Class III evidence that for patients with PCA, 2 software-based reading aids (single-word and double-word) improve reading accuracy. © 2015 American Academy of Neurology.

Facilitating text reading in posterior cortical atrophy

PubMed Central

Rajdev, Kishan; Shakespeare, Timothy J.; Leff, Alexander P.; Crutch, Sebastian J.

2015-01-01

Objective: We report (1) the quantitative investigation of text reading in posterior cortical atrophy (PCA), and (2) the effects of 2 novel software-based reading aids that result in dramatic improvements in the reading ability of patients with PCA. Methods: Reading performance, eye movements, and fixations were assessed in patients with PCA and typical Alzheimer disease and in healthy controls (experiment 1). Two reading aids (single- and double-word) were evaluated based on the notion that reducing the spatial and oculomotor demands of text reading might support reading in PCA (experiment 2). Results: Mean reading accuracy in patients with PCA was significantly worse (57%) compared with both patients with typical Alzheimer disease (98%) and healthy controls (99%); spatial aspects of passages were the primary determinants of text reading ability in PCA. Both aids led to considerable gains in reading accuracy (PCA mean reading accuracy: single-word reading aid = 96%; individual patient improvement range: 6%–270%) and self-rated measures of reading. Data suggest a greater efficiency of fixations and eye movements under the single-word reading aid in patients with PCA. Conclusions: These findings demonstrate how neurologic characterization of a neurodegenerative syndrome (PCA) and detailed cognitive analysis of an important everyday skill (reading) can combine to yield aids capable of supporting important everyday functional abilities. Classification of evidence: This study provides Class III evidence that for patients with PCA, 2 software-based reading aids (single-word and double-word) improve reading accuracy. PMID:26138948

Principal components analysis in clinical studies.

PubMed

Zhang, Zhongheng; Castelló, Adela

2017-09-01

In multivariate analysis, independent variables are usually correlated to each other which can introduce multicollinearity in the regression models. One approach to solve this problem is to apply principal components analysis (PCA) over these variables. This method uses orthogonal transformation to represent sets of potentially correlated variables with principal components (PC) that are linearly uncorrelated. PCs are ordered so that the first PC has the largest possible variance and only some components are selected to represent the correlated variables. As a result, the dimension of the variable space is reduced. This tutorial illustrates how to perform PCA in R environment, the example is a simulated dataset in which two PCs are responsible for the majority of the variance in the data. Furthermore, the visualization of PCA is highlighted.

Comparative preclinical evaluation of 68Ga-NODAGA and 68Ga-HBED-CC conjugated procainamide in melanoma imaging.

PubMed

Trencsényi, György; Dénes, Noémi; Nagy, Gábor; Kis, Adrienn; Vida, András; Farkas, Flóra; Szabó, Judit P; Kovács, Tünde; Berényi, Ervin; Garai, Ildikó; Bai, Péter; Hunyadi, János; Kertész, István

2017-05-30

Malignant melanoma is the most aggressive form of skin cancer. The early detection of primary melanoma tumors and metastases using non-invasive PET imaging determines the outcome of this disease. Previous studies have shown that benzamide derivatives (e.g. procainamide) conjugated with PET radionuclides specifically bind to melanin pigment of melanoma tumors. 68 Ga chelating agents can have high influence on physiological properties of 68 Ga labeled bioactive molecules, as was experienced during the application of HBED-CC on PSMA ligand. The aim of this study was to assess this concept in the case of the melanin specific procaindamide (PCA) and to compare the melanin specificity of 68 Ga-labeled PCA using HBED-CC and NODAGA chelators under in vitro and in vivo conditions. Procainamide (PCA) was conjugated with HBED-CC and NODAGA chelators and was labeled with Ga-68. The melanin specificity of 68 Ga-HBED-CC-PCA and 68 Ga-NODAGA-PCA was investigated in vitro and in vivo using amelanotic (MELUR and A375) and melanin containing (B16-F10) melanoma cell lines. Tumor-bearing mice were prepared by subcutaneous injection of B16-F10, MELUR and A375 melanoma cells into C57BL/6 and SCID mice. 21±2days after tumor cell inoculation and 90min after intravenous injection of the 68 Ga-labelledlabeled radiopharmacons whole body PET/MRI scans were performed. 68 Ga-NODAGA-PCA and 68 Ga-HBED-CC-PCA were produced with excellent radiochemical purity (98%). In vitro experiments demonstrated that after 30 and 90min incubation time 68 Ga-NODAGA-PCA uptake of B16-F10 cells was significantly (p≤0.01) higher than the 68 Ga-HBED-CC-conjugated PCA accumulation in the same cell line. Furthermore, significant difference (p≤0.01 and 0.05) was found between the uptake of melanin negative and positive cell lines using 68 Ga-NODAGA-PCA and 68 Ga-HBED-CC-PCA. In vivo PET/MRI studies using tumor models revealed significantly (p≤0.01) higher 68 Ga-NODAGA-PCA uptake (SUVmean: 0.46±0.05, SUVmax: 1.96±0.25,T/M ratio: 40.7±4.23) in B16-F10 tumors in contrast to 68 Ga-HBED-CC-PCA where the SUVmean, SUVmax and T/M ratio were 0.13±0.01, 0.56±0.11 and 11.43±1.24, respectively. Melanin specific PCA conjugated with NODAGA chelator showed higher specific binding properties than conjugated with HBED-CC. The chemical properties of the bifunctional chelators used for 68 Ga-labeling of PCA determine the biological behaviour of the probes. Due to the high specificity and sensitivity 68 Ga-labeled PCA molecules are promising radiotracers in melanoma imaging. Copyright © 2017 Elsevier B.V. All rights reserved.

Selecting predictors for discriminant analysis of species performance: an example from an amphibious softwater plant.

PubMed

Vanderhaeghe, F; Smolders, A J P; Roelofs, J G M; Hoffmann, M

2012-03-01

Selecting an appropriate variable subset in linear multivariate methods is an important methodological issue for ecologists. Interest often exists in obtaining general predictive capacity or in finding causal inferences from predictor variables. Because of a lack of solid knowledge on a studied phenomenon, scientists explore predictor variables in order to find the most meaningful (i.e. discriminating) ones. As an example, we modelled the response of the amphibious softwater plant Eleocharis multicaulis using canonical discriminant function analysis. We asked how variables can be selected through comparison of several methods: univariate Pearson chi-square screening, principal components analysis (PCA) and step-wise analysis, as well as combinations of some methods. We expected PCA to perform best. The selected methods were evaluated through fit and stability of the resulting discriminant functions and through correlations between these functions and the predictor variables. The chi-square subset, at P < 0.05, followed by a step-wise sub-selection, gave the best results. In contrast to expectations, PCA performed poorly, as so did step-wise analysis. The different chi-square subset methods all yielded ecologically meaningful variables, while probable noise variables were also selected by PCA and step-wise analysis. We advise against the simple use of PCA or step-wise discriminant analysis to obtain an ecologically meaningful variable subset; the former because it does not take into account the response variable, the latter because noise variables are likely to be selected. We suggest that univariate screening techniques are a worthwhile alternative for variable selection in ecology. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.

Detection and Characterization of Ground Displacement Sources from Variational Bayesian Independent Component Analysis of GPS Time Series

NASA Astrophysics Data System (ADS)

Gualandi, A.; Serpelloni, E.; Belardinelli, M. E.

2014-12-01

A critical point in the analysis of ground displacements time series is the development of data driven methods that allow to discern and characterize the different sources that generate the observed displacements. A widely used multivariate statistical technique is the Principal Component Analysis (PCA), which allows to reduce the dimensionality of the data space maintaining most of the variance of the dataset explained. It reproduces the original data using a limited number of Principal Components, but it also shows some deficiencies. Indeed, PCA does not perform well in finding the solution to the so-called Blind Source Separation (BSS) problem, i.e. in recovering and separating the original sources that generated the observed data. This is mainly due to the assumptions on which PCA relies: it looks for a new Euclidean space where the projected data are uncorrelated. Usually, the uncorrelation condition is not strong enough and it has been proven that the BSS problem can be tackled imposing on the components to be independent. The Independent Component Analysis (ICA) is, in fact, another popular technique adopted to approach this problem, and it can be used in all those fields where PCA is also applied. An ICA approach enables us to explain the time series imposing a fewer number of constraints on the model, and to reveal anomalies in the data such as transient signals. However, the independence condition is not easy to impose, and it is often necessary to introduce some approximations. To work around this problem, we use a variational bayesian ICA (vbICA) method, which models the probability density function (pdf) of each source signal using a mix of Gaussian distributions. This technique allows for more flexibility in the description of the pdf of the sources, giving a more reliable estimate of them. Here we present the application of the vbICA technique to GPS position time series. First, we use vbICA on synthetic data that simulate a seismic cycle (interseismic + coseismic + postseismic + seasonal + noise), and study the ability of the algorithm to recover the original (known) sources of deformation. Secondly, we apply vbICA to different tectonically active scenarios, such as earthquakes in central and northern Italy, as well as the study of slow slip events in Cascadia.

Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Pin-Yu; Choudhury, Sutanay; Hero, Alfred

Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles ofmore » graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.« less

Racism, Racial Resilience, and African American Youth Development: Person-Centered Analysis as a Tool to Promote Equity and Justice.

PubMed

Neblett, Enrique W; Sosoo, Effua E; Willis, Henry A; Bernard, Donte L; Bae, Jiwoon; Billingsley, Janelle T

Racism constitutes a significant risk to the healthy development of African American youth. Fortunately, however, not all youth who experience racism evidence negative developmental outcomes. In this chapter, we examine person-centered analysis (PCA)-a quantitative technique that investigates how variables combine across individuals-as a useful tool for elucidating racial and ethnic protective processes that mitigate the negative impact of racism. We review recent studies employing PCA in examinations of racial identity, racial socialization, and other race-related experiences, as well as how these constructs correlate with and impact African American youth development. We also consider challenges and limitations of PCA and conclude with a discussion of future research and how PCA might be used to promote equity and justice for African American and other racial and ethnic minority youth who experience racism. © 2016 Elsevier Inc. All rights reserved.

Visuoconstructional Impairment in Subtypes of Mild Cognitive Impairment

PubMed Central

Ahmed, Samrah; Brennan, Laura; Eppig, Joel; Price, Catherine C.; Lamar, Melissa; Delano-Wood, Lisa; Bangen, Katherine J.; Edmonds, Emily C.; Clark, Lindsey; Nation, Daniel A.; Jak, Amy; Au, Rhoda; Swenson, Rodney; Bondi, Mark W.; Libon, David J.

2018-01-01

Clock Drawing Test performance was examined alongside other neuropsychological tests in mild cognitive impairment (MCI). We tested the hypothesis that clock-drawing errors are related to executive impairment. The current research examined 86 patients with MCI for whom, in prior research, cluster analysis was used to sort patients into dysexecutive (dMCI, n=22), amnestic (aMCI, n=13), and multi-domain (mMCI, n=51) subtypes. First, principal components analysis (PCA) and linear regression examined relations between clock-drawing errors and neuropsychological test performance independent of MCI subtype. Second, between-group differences were assessed with analysis of variance (ANOVA) where MCI subgroups were compared to normal controls (NC). PCA yielded a 3-group solution. Contrary to expectations, clock-drawing errors loaded with lower performance on naming/lexical retrieval, rather than with executive tests. Regression analyses found increasing clock-drawing errors to command were associated with worse performance only on naming/lexical retrieval tests. ANOVAs revealed no differences in clock-drawing errors between dMCI versus mMCI or aMCI versus NCs. Both the dMCI and mMCI groups generated more clock-drawing errors than the aMCI and NC groups in the command condition. In MCI, language-related skills contribute to clock-drawing impairment. PMID:26397732

Recognizing different tissues in human fetal femur cartilage by label-free Raman microspectroscopy

NASA Astrophysics Data System (ADS)

Kunstar, Aliz; Leijten, Jeroen; van Leuveren, Stefan; Hilderink, Janneke; Otto, Cees; van Blitterswijk, Clemens A.; Karperien, Marcel; van Apeldoorn, Aart A.

2012-11-01

Traditionally, the composition of bone and cartilage is determined by standard histological methods. We used Raman microscopy, which provides a molecular "fingerprint" of the investigated sample, to detect differences between the zones in human fetal femur cartilage without the need for additional staining or labeling. Raman area scans were made from the (pre)articular cartilage, resting, proliferative, and hypertrophic zones of growth plate and endochondral bone within human fetal femora. Multivariate data analysis was performed on Raman spectral datasets to construct cluster images with corresponding cluster averages. Cluster analysis resulted in detection of individual chondrocyte spectra that could be separated from cartilage extracellular matrix (ECM) spectra and was verified by comparing cluster images with intensity-based Raman images for the deoxyribonucleic acid/ribonucleic acid (DNA/RNA) band. Specific dendrograms were created using Ward's clustering method, and principal component analysis (PCA) was performed with the separated and averaged Raman spectra of cells and ECM of all measured zones. Overall (dis)similarities between measured zones were effectively visualized on the dendrograms and main spectral differences were revealed by PCA allowing for label-free detection of individual cartilaginous zones and for label-free evaluation of proper cartilaginous matrix formation for future tissue engineering and clinical purposes.

Ion Mobility-Mass Spectrometry Analysis of Serum N-linked Glycans from Esophageal Adenocarcinoma Phenotypes

PubMed Central

Gaye, M. M.; Valentine, S. J.; Hu, Y.; Mirjankar, N.; Hammoud, Z. T.; Mechref, Y.; Lavine, B. K.; Clemmer, D. E.

2012-01-01

Three disease phenotypes, Barrett’s esophagus (BE), high-grade dysplasia (HGD), esophageal adenocarcinoma (EAC), and a set of normal control (NC) serum samples are examined using a combination of ion mobility spectrometry (IMS), mass spectrometry (MS) and principal component analysis (PCA) techniques. Samples from a total of 136 individuals were examined, including: 7 characterized as BE, 12 as HGD, 56 as EAC and 61 as NC. In typical datasets it was possible to assign ~20 to 30 glycan ions based on MS measurements. Ion mobility distributions for these ions show multiple features. In some cases, such as the [S1H5N4+3Na]3+ and [S1F1H5N4+3Na]3+ glycan ions, the ratio of intensities of high-mobility features to low-mobility features vary significantly for different groups. The degree to which such variations in mobility profiles can be used to distinguish phenotypes is evaluated for eleven N-linked glycan ions. An outlier analysis on each sample class followed by an unsupervised PCA using a genetic algorithm for pattern recognition reveals that EAC samples are separated from NC samples based on 46 features originating from the 11-glycan composite IMS distribution. PMID:23126309

Characterization of cytochrome c as marker for retinal cell degeneration by uv/vis spectroscopic imaging

NASA Astrophysics Data System (ADS)

Hollmach, Julia; Schweizer, Julia; Steiner, Gerald; Knels, Lilla; Funk, Richard H. W.; Thalheim, Silko; Koch, Edmund

2011-07-01

Retinal diseases like age-related macular degeneration have become an important cause of visual loss depending on increasing life expectancy and lifestyle habits. Due to the fact that no satisfying treatment exists, early diagnosis and prevention are the only possibilities to stop the degeneration. The protein cytochrome c (cyt c) is a suitable marker for degeneration processes and apoptosis because it is a part of the respiratory chain and involved in the apoptotic pathway. The determination of the local distribution and oxidative state of cyt c in living cells allows the characterization of cell degeneration processes. Since cyt c exhibits characteristic absorption bands between 400 and 650 nm wavelength, uv/vis in situ spectroscopic imaging was used for its characterization in retinal ganglion cells. The large amount of data, consisting of spatial and spectral information, was processed by multivariate data analysis. The challenge consists in the identification of the molecular information of cyt c. Baseline correction, principle component analysis (PCA) and cluster analysis (CA) were performed in order to identify cyt c within the spectral dataset. The combination of PCA and CA reveals cyt c and its oxidative state. The results demonstrate that uv/vis spectroscopic imaging in conjunction with sophisticated multivariate methods is a suitable tool to characterize cyt c under in situ conditions.

A new scale for disaster nursing core competencies: Development and psychometric testing.

PubMed

Al Thobaity, Abdulellah; Williams, Brett; Plummer, Virginia

2016-02-01

All nurses must have core competencies in preparing for, responding to and recovering from a disaster. In the Kingdom of Saudi Arabia (KSA), as in many other countries, disaster nursing core competencies are not fully understood and lack reliable, validated tools. Thus, it is imperative to develop a scale for exploring disaster nursing core competencies, roles and barriers in the KSA. This study's objective is to develop a valid, reliable scale that identifies and explores core competencies of disaster nursing, nurses' roles in disaster management and barriers to developing disaster nursing in the KSA. This study developed a new scale testing its validity and reliability. A principal component analysis (PCA) was used to develop and test psychometric properties of the new scale. The PCA used a purposive sample of nurses from emergency departments in two hospitals in the KSA. Participants rated 93 paper-based, self-report questionnaire items from 1 to 10 on a Likert scale. PCA using Varimax rotation was conducted to explore factors emerging from responses. The study's participants were 132 nurses (66% response rate). PCA of the 93 questionnaire items revealed 49 redundant items (which were deleted) and 3 factors with eigenvalues of >1. The remaining 44 items accounted for 77.3% of the total variance. The overall Cronbach's alpha was 0.96 for all factors: 0.98 for Factor 1, 0.92 for Factor 2 and 0.86 for Factor 3. This study provided a validated, reliable scale for exploring nurses' core competencies, nurses' roles and barriers to developing disaster nursing in the KSA. The new scale has many implications, such as for improving education, planning and curricula. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Multiscale 3D Shape Analysis using Spherical Wavelets

PubMed Central

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2013-01-01

Shape priors attempt to represent biological variations within a population. When variations are global, Principal Component Analysis (PCA) can be used to learn major modes of variation, even from a limited training set. However, when significant local variations exist, PCA typically cannot represent such variations from a small training set. To address this issue, we present a novel algorithm that learns shape variations from data at multiple scales and locations using spherical wavelets and spectral graph partitioning. Our results show that when the training set is small, our algorithm significantly improves the approximation of shapes in a testing set over PCA, which tends to oversmooth data. PMID:16685992

Multiscale 3D shape analysis using spherical wavelets.

PubMed

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen R

2005-01-01

Shape priors attempt to represent biological variations within a population. When variations are global, Principal Component Analysis (PCA) can be used to learn major modes of variation, even from a limited training set. However, when significant local variations exist, PCA typically cannot represent such variations from a small training set. To address this issue, we present a novel algorithm that learns shape variations from data at multiple scales and locations using spherical wavelets and spectral graph partitioning. Our results show that when the training set is small, our algorithm significantly improves the approximation of shapes in a testing set over PCA, which tends to oversmooth data.

PCA3 noncoding RNA is involved in the control of prostate-cancer cell survival and modulates androgen receptor signaling

PubMed Central

2012-01-01

Background PCA3 is a non-coding RNA (ncRNA) that is highly expressed in prostate cancer (PCa) cells, but its functional role is unknown. To investigate its putative function in PCa biology, we used gene expression knockdown by small interference RNA, and also analyzed its involvement in androgen receptor (AR) signaling. Methods LNCaP and PC3 cells were used as in vitro models for these functional assays, and three different siRNA sequences were specifically designed to target PCA3 exon 4. Transfected cells were analyzed by real-time qRT-PCR and cell growth, viability, and apoptosis assays. Associations between PCA3 and the androgen-receptor (AR) signaling pathway were investigated by treating LNCaP cells with 100 nM dihydrotestosterone (DHT) and with its antagonist (flutamide), and analyzing the expression of some AR-modulated genes (TMPRSS2, NDRG1, GREB1, PSA, AR, FGF8, CdK1, CdK2 and PMEPA1). PCA3 expression levels were investigated in different cell compartments by using differential centrifugation and qRT-PCR. Results LNCaP siPCA3-transfected cells significantly inhibited cell growth and viability, and increased the proportion of cells in the sub G0/G1 phase of the cell cycle and the percentage of pyknotic nuclei, compared to those transfected with scramble siRNA (siSCr)-transfected cells. DHT-treated LNCaP cells induced a significant upregulation of PCA3 expression, which was reversed by flutamide. In siPCA3/LNCaP-transfected cells, the expression of AR target genes was downregulated compared to siSCr-transfected cells. The siPCA3 transfection also counteracted DHT stimulatory effects on the AR signaling cascade, significantly downregulating expression of the AR target gene. Analysis of PCA3 expression in different cell compartments provided evidence that the main functional roles of PCA3 occur in the nuclei and microsomal cell fractions. Conclusions Our findings suggest that the ncRNA PCA3 is involved in the control of PCa cell survival, in part through modulating AR signaling, which may raise new possibilities of using PCA3 knockdown as an additional therapeutic strategy for PCa control. PMID:23130941

Optimizing the clinical utility of PCA3 to diagnose prostate cancer in initial prostate biopsy.

PubMed

Rubio-Briones, Jose; Borque, Angel; Esteban, Luis M; Casanova, Juan; Fernandez-Serra, Antonio; Rubio, Luis; Casanova-Salas, Irene; Sanz, Gerardo; Domínguez-Escrig, Jose; Collado, Argimiro; Gómez-Ferrer, Alvaro; Iborra, Inmaculada; Ramírez-Backhaus, Miguel; Martínez, Francisco; Calatrava, Ana; Lopez-Guerrero, Jose A

2015-09-11

PCA3 has been included in a nomogram outperforming previous clinical models for the prediction of any prostate cancer (PCa) and high grade PCa (HGPCa) at the initial prostate biopsy (IBx). Our objective is to validate such IBx-specific PCA3-based nomogram. We also aim to optimize the use of this nomogram in clinical practice through the definition of risk groups. Independent external validation. Clinical and biopsy data from a contemporary cohort of 401 men with the same inclusion criteria to those used to build up the reference's nomogram in IBx. The predictive value of the nomogram was assessed by means of calibration curves and discrimination ability through the area under the curve (AUC). Clinical utility of the nomogram was analyzed by choosing thresholds points that minimize the overlapping between probability density functions (PDF) in PCa and no PCa and HGPCa and no HGPCa groups, and net benefit was assessed by decision curves. We detect 28% of PCa and 11 % of HGPCa in IBx, contrasting to the 46 and 20% at the reference series. Due to this, there is an overestimation of the nomogram probabilities shown in the calibration curve for PCa. The AUC values are 0.736 for PCa (C.I.95%:0.68-0.79) and 0.786 for HGPCa (C.I.95%:0.71-0.87) showing an adequate discrimination ability. PDF show differences in the distributions of nomogram probabilities in PCa and not PCa patient groups. A minimization of the overlapping between these curves confirms the threshold probability of harboring PCa >30 % proposed by Hansen is useful to indicate a IBx, but a cut-off > 40% could be better in series of opportunistic screening like ours. Similar results appear in HGPCa analysis. The decision curve also shows a net benefit of 6.31% for the threshold probability of 40%. PCA3 is an useful tool to select patients for IBx. Patients with a calculated probability of having PCa over 40% should be counseled to undergo an IBx if opportunistic screening is required.

Modulation of lateral and longitudinal interdimeric interactions in microtubule models by Laulimalide and Peloruside A association: A molecular modeling approach on the mechanism of microtubule stabilizing agents.

PubMed

Zúñiga, Matías A; Alderete, Joel B; Jaña, Gonzalo A; Fernandez, Pedro A; Ramos, Maria J; Jiménez, Verónica A

2018-05-01

Laulimalide (LAU) and Peloruside A (PLA) are non-taxane microtubule stabilizing agents with promising antimitotic properties. These ligands promote the assembly of microtubules (MTs) by targeting a unique binding site on β-tubulin. The X-ray structure for LAU/PLA-tubulin association was recently elucidated, but little information is available regarding the role of these ligands as modulators of interdimeric interactions across MTs. Herein, we report the use of molecular dynamics (MD), principal component analysis (PCA), MM/GBSA-binding free energy calculations, and computational alanine scanning mutagenesis (ASM) to examine effect of LAU/PLA association on lateral and longitudinal contacts between tubulin dimers in reduced MT models. MD and PCA results revealed that LAU/PLA exerts a strong restriction of lateral and longitudinal interdimeric motions, thus enabling the stabilization of the MT lattice. Besides structural effects, LAU/PLA induces a substantial strengthening of longitudinal interdimeric interactions, whereas lateral contacts are less affected by these ligands, as revealed by MM/GBSA and ASM calculations. These results are valuable to increase understanding about the molecular features involved in MT stabilization by LAU/PLA, and to design novel compounds capable of emulating the mode of action of these ligands. © 2018 John Wiley & Sons A/S.

Genetic variation, population structure and linkage disequilibrium in Switchgrass with ISSR, SCoT and EST-SSR markers.

PubMed

Zhang, Yu; Yan, Haidong; Jiang, Xiaomei; Wang, Xiaoli; Huang, Linkai; Xu, Bin; Zhang, Xinquan; Zhang, Lexin

2016-01-01

To evaluate genetic variation, population structure, and the extent of linkage disequilibrium (LD), 134 switchgrass ( Panicum virgatum L.) samples were analyzed with 51 markers, including 16 ISSRs, 20 SCoTs, and 15 EST-SSRs. In this study, a high level of genetic variation was observed in the switchgrass samples and they had an average Nei's gene diversity index (H) of 0.311. A total of 793 bands were obtained, of which 708 (89.28 %) were polymorphic. Using a parameter marker index (MI), the efficiency of the three types of markers (ISSR, SCoT, and EST-SSR) in the study were compared and we found that SCoT had a higher marker efficiency than the other two markers. The 134 switchgrass samples could be divided into two sub-populations based on STRUCTURE, UPGMA clustering, and principal coordinate analyses (PCA), and upland and lowland ecotypes could be separated by UPGMA clustering and PCA analyses. Linkage disequilibrium analysis revealed an average r 2 of 0.035 across all 51 markers, indicating a trend of higher LD in sub-population 2 than that in sub-population 1 ( P  < 0.01). The population structure revealed in this study will guide the design of future association studies using these switchgrass samples.

Volatile compounds in cryptic species of the Aneura pinguis complex and Aneura maxima (Marchantiophyta, Metzgeriidae).

PubMed

Wawrzyniak, Rafał; Wasiak, Wiesław; Bączkiewicz, Alina; Buczkowska, Katarzyna

2014-09-01

Aneura pinguis is one of the liverwort species complexes that consist of several cryptic species. Ten samples collected from different regions in Poland are in the focus of our research. Eight of the A. pinguis complex belonging to four cryptic species (A, B, C, E) and two samples of closely related species Aneura maxima were tested for the composition of volatile compounds. The HS-SPME technique coupled to GC/FID and GC/MS analysis has been applied. The fiber coated with DVB/CAR/PDMS has been used. The results of the present study, revealed the qualitative and quantitative differences in the composition of the volatile compounds between the studied species. Mainly they are from the group of sesquiterpenoids, oxygenated sesquiterpenoids and aliphatic hydrocarbons. The statistical methods (CA and PCA) showed that detected volatile compounds allow to distinguish cryptic species of A. pinguis. All examined cryptic species of the A. pinguis complex differ from A. maxima. Species A and E of A. pinguis, in CA and PCA, form separate clusters remote from two remaining cryptic species of A. pinguis (B and C) and A. maxima. Relationship between the cryptic species appeared from the chemical studies are in accordance with that revealed on the basis of DNA sequences. Copyright © 2014 Elsevier Ltd. All rights reserved.

Fine-scale population genetic structure of arctic foxes (Vulpes lagopus) in the High Arctic.

PubMed

Lai, Sandra; Quiles, Adrien; Lambourdière, Josie; Berteaux, Dominique; Lalis, Aude

2017-12-01

The arctic fox (Vulpes lagopus) is a circumpolar species inhabiting all accessible Arctic tundra habitats. The species forms a panmictic population over areas connected by sea ice, but recently, kin clustering and population differentiation were detected even in regions where sea ice was present. The purpose of this study was to examine the genetic structure of a population in the High Arctic using a robust panel of highly polymorphic microsatellites. We analyzed the genotypes of 210 individuals from Bylot Island, Nunavut, Canada, using 15 microsatellite loci. No pattern of isolation-by-distance was detected, but a spatial principal component analysis (sPCA) revealed the presence of genetic subdivisions. Overall, the sPCA revealed two spatially distinct genetic clusters corresponding to the northern and southern parts of the study area, plus another subdivision within each of these two clusters. The north-south genetic differentiation partly matched the distribution of a snow goose colony, which could reflect a preference for settling into familiar ecological environments. Secondary clusters may result from higher-order social structures (neighbourhoods) that use landscape features to delimit their borders. The cryptic genetic subdivisions found in our population may highlight ecological processes deserving further investigations in arctic foxes at larger, regional spatial scales.

2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications.

PubMed

Du, Qi-Shi; Wang, Shu-Qing; Xie, Neng-Zhong; Wang, Qing-Yan; Huang, Ri-Bo; Chou, Kuo-Chen

2017-09-19

A two-level principal component predictor (2L-PCA) was proposed based on the principal component analysis (PCA) approach. It can be used to quantitatively analyze various compounds and peptides about their functions or potentials to become useful drugs. One level is for dealing with the physicochemical properties of drug molecules, while the other level is for dealing with their structural fragments. The predictor has the self-learning and feedback features to automatically improve its accuracy. It is anticipated that 2L-PCA will become a very useful tool for timely providing various useful clues during the process of drug development.

The burden of urinary incontinence and urinary bother among elderly prostate cancer survivors.

PubMed

Kopp, Ryan P; Marshall, Lynn M; Wang, Patty Y; Bauer, Douglas C; Barrett-Connor, Elizabeth; Parsons, J Kellogg

2013-10-01

Data describing urinary health in elderly, community-dwelling prostate cancer (PCa) survivors are limited. To elucidate the prevalence of lower urinary tract symptoms, urinary bother, and incontinence in elderly PCa survivors compared with peers without PCa. A cross-sectional analysis of 5990 participants in the Osteoporotic Fractures in Men Research Group, a cohort study of community-dwelling men ≥ 65 yr. We characterized urinary health using self-reported urinary incontinence and the American Urological Association Symptom Index (AUA-SI). We compared urinary health measures according to type of PCa treatment in men with PCa and men without PCa using multivariate log-binomial regression to generate prevalence ratios (PRs). At baseline, 706 men (12%) reported a history of PCa, with a mean time since diagnosis of 6.3 yr. Of these men, 426 (60%) reported urinary incontinence. In adjusted analyses, observation (PR: 2.11; 95% confidence interval [CI], 1.22-3.65; p=0.007), surgery (PR: 4.41; 95% CI, 3.79-5.13; p<0.0001), radiation therapy (PR: 1.49; 95% CI, 1.06-2.08; p=0.02), and androgen-deprivation therapy (ADT) (PR: 2.02; 95% CI, 1.31-3.13; p=0.002) were each associated with daily incontinence. Daily incontinence risk increased with time since diagnosis independently of age. Observation (PR: 1.33; 95% CI, 1.00-1.78; p=0.05), surgery (PR: 1.25; 95% CI, 1.10-1.42; p=0.0008), and ADT (PR: 1.50; 95% CI, 1.26-1.79; p<0.0001) were associated with increased AUA-SI bother scores. Cancer stage and use of adjuvant or salvage therapies were not available for analysis. Compared with their peers without PCa, elderly PCa survivors had a two-fold to five-fold greater prevalence of urinary incontinence, which rose with increasing survivorship duration. Observation, surgery, and ADT were each associated with increased urinary bother. These data suggest a substantially greater burden of urinary health problems among elderly PCa survivors than previously recognized. Copyright © 2013 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Contribution made by multivariate curve resolution applied to gel permeation chromatography-Fourier transform infrared data for an in-depth characterization of styrene-butadiene rubber blends.

PubMed

Ruckebusch, C; Vilmin, F; Coste, N; Huvenne, J P

2008-07-01

We evaluate the contribution made by multivariate curve resolution-alternating least squares (MCR-ALS) for resolving gel permeation chromatography-Fourier transform infrared (GPC-FT-IR) data collected on butadiene rubber (BR) and styrene butadiene rubber (SBR) blends in order to access in-depth knowledge of polymers along the molecular weight distribution (MWD). In the BR-SBR case, individual polymers differ in chemical composition but share almost the same MWD. Principal component analysis (PCA) gives a general overview of the data structure and attests to the feasibility of modeling blends as a binary system. MCR-ALS is then performed. It allows resolving the chromatographic coelution and validates the chosen methodology. For SBR-SBR blends, the problem is more challenging since the individual elastomers present the same chemical composition. Rank deficiency is detected from the PCA data structure analysis. MCR-ALS is thus performed on column-wise augmented matrices. It brings very useful insight into the composition of the analyzed blends. In particular, a weak change in the composition of individual SBR in the MWD's lowest mass region is revealed.

Relationship between Composition and Toxicity of Motor Vehicle Emission Samples

PubMed Central

McDonald, Jacob D.; Eide, Ingvar; Seagrave, JeanClare; Zielinska, Barbara; Whitney, Kevin; Lawson, Douglas R.; Mauderly, Joe L.

2004-01-01

In this study we investigated the statistical relationship between particle and semivolatile organic chemical constituents in gasoline and diesel vehicle exhaust samples, and toxicity as measured by inflammation and tissue damage in rat lungs and mutagenicity in bacteria. Exhaust samples were collected from “normal” and “high-emitting” gasoline and diesel light-duty vehicles. We employed a combination of principal component analysis (PCA) and partial least-squares regression (PLS; also known as projection to latent structures) to evaluate the relationships between chemical composition of vehicle exhaust and toxicity. The PLS analysis revealed the chemical constituents covarying most strongly with toxicity and produced models predicting the relative toxicity of the samples with good accuracy. The specific nitro-polycyclic aromatic hydrocarbons important for mutagenicity were the same chemicals that have been implicated by decades of bioassay-directed fractionation. These chemicals were not related to lung toxicity, which was associated with organic carbon and select organic compounds that are present in lubricating oil. The results demonstrate the utility of the PCA/PLS approach for evaluating composition–response relationships in complex mixture exposures and also provide a starting point for confirming causality and determining the mechanisms of the lung effects. PMID:15531438

Baccharis dracunculifolia-based mouthrinse alters the exopolysaccharide structure in cariogenic biofilms.

PubMed

Aires, Carolina P; Sassaki, Guilherme L; Santana-Filho, Arquimedes P; Spadaro, Augusto C C; Cury, Jaime A

2016-03-01

Baccharis dracunculifolia is a native plant from Brazil with antimicrobial activity. The purpose of this study was to investigate whether a B. dracunculifolia-based mouthrinse (Bd) changes the structure of insoluble exopolysaccharides (IEPS) in Streptococcus mutans UA159 cariogenic biofilm. Biofilms were grown on glass slides and treated with Bd, its vehicle (VC), chlorhexidine digluconate (CHX), or saline solution (NaCl). Among the treatments, only CHX significantly reduced the biofilm biomass and bacterial viability (p<0.05). Gas chromatography-mass spectrometry and nuclear magnetic resonance analyses revealed that IEPS from the four biofilm samples were α- glucans containing different proportions of (1→6) and (1→3) glycosidic linkages. The structural differences among the four IEPS were compared by principal component analysis (PCA). PCA analysis indicated that IEPS from VC- and NaCl-treated biofilms were structurally similar to each other. Compared with the control, IEPS from Bd- and CHX-treated biofilms were structurally different and had distinct chemical profiles. In summary, the fact that Bd changed the IEPS chemical composition indicates that this mouthrinse may affect the cariogenic properties of the S. mutans biofilm formed. Copyright © 2015. Published by Elsevier B.V.

A hybrid sensing approach for pure and adulterated honey classification.

PubMed

Subari, Norazian; Mohamad Saleh, Junita; Md Shakaff, Ali Yeon; Zakaria, Ammar

2012-10-17

This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.

Epileptic seizure detection in EEG signal with GModPCA and support vector machine.

PubMed

Jaiswal, Abeg Kumar; Banka, Haider

2017-01-01

Epilepsy is one of the most common neurological disorders caused by recurrent seizures. Electroencephalograms (EEGs) record neural activity and can detect epilepsy. Visual inspection of an EEG signal for epileptic seizure detection is a time-consuming process and may lead to human error; therefore, recently, a number of automated seizure detection frameworks were proposed to replace these traditional methods. Feature extraction and classification are two important steps in these procedures. Feature extraction focuses on finding the informative features that could be used for classification and correct decision-making. Therefore, proposing effective feature extraction techniques for seizure detection is of great significance. Principal Component Analysis (PCA) is a dimensionality reduction technique used in different fields of pattern recognition including EEG signal classification. Global modular PCA (GModPCA) is a variation of PCA. In this paper, an effective framework with GModPCA and Support Vector Machine (SVM) is presented for epileptic seizure detection in EEG signals. The feature extraction is performed with GModPCA, whereas SVM trained with radial basis function kernel performed the classification between seizure and nonseizure EEG signals. Seven different experimental cases were conducted on the benchmark epilepsy EEG dataset. The system performance was evaluated using 10-fold cross-validation. In addition, we prove analytically that GModPCA has less time and space complexities as compared to PCA. The experimental results show that EEG signals have strong inter-sub-pattern correlations. GModPCA and SVM have been able to achieve 100% accuracy for the classification between normal and epileptic signals. Along with this, seven different experimental cases were tested. The classification results of the proposed approach were better than were compared the results of some of the existing methods proposed in literature. It is also found that the time and space complexities of GModPCA are less as compared to PCA. This study suggests that GModPCA and SVM could be used for automated epileptic seizure detection in EEG signal.

Gabor-based kernel PCA with fractional power polynomial models for face recognition.

PubMed

Liu, Chengjun

2004-05-01

This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power polynomial models, the Gabor wavelet-based PCA method, and the Gabor wavelet-based kernel PCA method with polynomial kernels.

Multivariate Analysis of Fruit Antioxidant Activities of Blackberry Treated with 1-Methylcyclopropene or Vacuum Precooling

PubMed Central

Li, Jian; Ma, Guowei; Ma, Lin; Bao, Xiaolin; Li, Liping; Zhao, Qian

2018-01-01

Effects of 1-methylcyclopropene (1-MCP) and vacuum precooling on quality and antioxidant properties of blackberries (Rubus spp.) were evaluated using one-way analysis of variance, principal component analysis (PCA), partial least squares (PLS), and path analysis. Results showed that the activities of antioxidant enzymes were enhanced by both 1-MCP treatment and vacuum precooling. PCA could discriminate 1-MCP treated fruit and the vacuum precooled fruit and showed that the radical-scavenging activities in vacuum precooled fruit were higher than those in 1-MCP treated fruit. The scores of PCA showed that H2O2 content was the most important variables of blackberry fruit. PLSR results showed that peroxidase (POD) activity negatively correlated with H2O2 content. The results of path coefficient analysis indicated that glutathione (GSH) also had an indirect effect on H2O2 content. PMID:29487622

Application of principal component analysis (PCA) as a sensory assessment tool for fermented food products.

PubMed

Ghosh, Debasree; Chattopadhyay, Parimal

2012-06-01

The objective of the work was to use the method of quantitative descriptive analysis (QDA) to describe the sensory attributes of the fermented food products prepared with the incorporation of lactic cultures. Panellists were selected and trained to evaluate various attributes specially color and appearance, body texture, flavor, overall acceptability and acidity of the fermented food products like cow milk curd and soymilk curd, idli, sauerkraut and probiotic ice cream. Principal component analysis (PCA) identified the six significant principal components that accounted for more than 90% of the variance in the sensory attribute data. Overall product quality was modelled as a function of principal components using multiple least squares regression (R (2) = 0.8). The result from PCA was statistically analyzed by analysis of variance (ANOVA). These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring the fermented food product attributes that are important for consumer acceptability.

Fixed Eigenvector Analysis of Thermographic NDE Data

NASA Technical Reports Server (NTRS)

Cramer, K. Elliott; Winfree, William P.

2011-01-01

Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. This paper will discuss an alternative method of analysis that has been developed where a predetermined set of eigenvectors is used to process the thermal data from both reinforced carbon-carbon (RCC) and graphiteepoxy honeycomb materials. These eigenvectors can be generated either from an analytic model of the thermal response of the material system under examination, or from a large set of experimental data. This paper provides the details of the analytic model, an overview of the PCA process, as well as a quantitative signal-to-noise comparison of the results of performing both conventional PCA and fixed eigenvector analysis on thermographic data from two specimens, one Reinforced Carbon-Carbon with flat bottom holes and the second a sandwich construction with graphite-epoxy face sheets and aluminum honeycomb core.

An in vitro investigation on friction generated by ceramic brackets.

PubMed

Tecco, Simona; Teté, Stefano; Festa, Mario; Festa, Felice

2010-01-01

To compare friction (F) of conventional and ceramic brackets (0.022-inch slot) using a model that tests the sliding of the archwire through 10 aligned brackets. Polycrystalline alumina brackets (PCAs), PCA brackets with a stainless steel slot (PCA-M), and monocrystalline sapphire brackets (MCS) were tested under elastic ligatures using various archwires in dry and wet (saliva) states. Conventional stainless steel brackets were used as controls. In both dry and wet states, PCA and MCS brackets expressed a statistically significant higher F value with respect to stainless steel and PCA-M brackets when combined with the rectangular archwires (P<.01). PCA brackets showed significantly higher friction than MCS brackets (P<.01) when coupled with 0.014 x 0.025-inch nickel-titanium (Ni-Ti) archwire. SEM analysis showed differences in the surfaces among stainless steel, MCS, PCA-M, and PCA brackets. In the wet state, the mean F values were generally higher than in the dry state. PCA brackets showed significantly higher F than MCS brackets only when combined with 0.014 x 0.025-inch Ni-Ti archwires. Thus, in this study, a 10 aligned-brackets study model showed similar results when compared to a single bracket system except for friction level with 0.014 × 0.025-inch Ni-Ti archwires. © 2011 BY QUINTESSENCE PUBLISHING CO, INC.

Perturbational formulation of principal component analysis in molecular dynamics simulation.

PubMed

Koyama, Yohei M; Kobayashi, Tetsuya J; Tomoda, Shuji; Ueda, Hiroki R

2008-10-01

Conformational fluctuations of a molecule are important to its function since such intrinsic fluctuations enable the molecule to respond to the external environmental perturbations. For extracting large conformational fluctuations, which predict the primary conformational change by the perturbation, principal component analysis (PCA) has been used in molecular dynamics simulations. However, several versions of PCA, such as Cartesian coordinate PCA and dihedral angle PCA (dPCA), are limited to use with molecules with a single dominant state or proteins where the dihedral angle represents an important internal coordinate. Other PCAs with general applicability, such as the PCA using pairwise atomic distances, do not represent the physical meaning clearly. Therefore, a formulation that provides general applicability and clearly represents the physical meaning is yet to be developed. For developing such a formulation, we consider the conformational distribution change by the perturbation with arbitrary linearly independent perturbation functions. Within the second order approximation of the Kullback-Leibler divergence by the perturbation, the PCA can be naturally interpreted as a method for (1) decomposing a given perturbation into perturbations that independently contribute to the conformational distribution change or (2) successively finding the perturbation that induces the largest conformational distribution change. In this perturbational formulation of PCA, (i) the eigenvalue measures the Kullback-Leibler divergence from the unperturbed to perturbed distributions, (ii) the eigenvector identifies the combination of the perturbation functions, and (iii) the principal component determines the probability change induced by the perturbation. Based on this formulation, we propose a PCA using potential energy terms, and we designate it as potential energy PCA (PEPCA). The PEPCA provides both general applicability and clear physical meaning. For demonstrating its power, we apply the PEPCA to an alanine dipeptide molecule in vacuum as a minimal model of a nonsingle dominant conformational biomolecule. The first and second principal components clearly characterize two stable states and the transition state between them. Positive and negative components with larger absolute values of the first and second eigenvectors identify the electrostatic interactions, which stabilize or destabilize each stable state and the transition state. Our result therefore indicates that PCA can be applied, by carefully selecting the perturbation functions, not only to identify the molecular conformational fluctuation but also to predict the conformational distribution change by the perturbation beyond the limitation of the previous methods.

Perturbational formulation of principal component analysis in molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Koyama, Yohei M.; Kobayashi, Tetsuya J.; Tomoda, Shuji; Ueda, Hiroki R.

2008-10-01

Conformational fluctuations of a molecule are important to its function since such intrinsic fluctuations enable the molecule to respond to the external environmental perturbations. For extracting large conformational fluctuations, which predict the primary conformational change by the perturbation, principal component analysis (PCA) has been used in molecular dynamics simulations. However, several versions of PCA, such as Cartesian coordinate PCA and dihedral angle PCA (dPCA), are limited to use with molecules with a single dominant state or proteins where the dihedral angle represents an important internal coordinate. Other PCAs with general applicability, such as the PCA using pairwise atomic distances, do not represent the physical meaning clearly. Therefore, a formulation that provides general applicability and clearly represents the physical meaning is yet to be developed. For developing such a formulation, we consider the conformational distribution change by the perturbation with arbitrary linearly independent perturbation functions. Within the second order approximation of the Kullback-Leibler divergence by the perturbation, the PCA can be naturally interpreted as a method for (1) decomposing a given perturbation into perturbations that independently contribute to the conformational distribution change or (2) successively finding the perturbation that induces the largest conformational distribution change. In this perturbational formulation of PCA, (i) the eigenvalue measures the Kullback-Leibler divergence from the unperturbed to perturbed distributions, (ii) the eigenvector identifies the combination of the perturbation functions, and (iii) the principal component determines the probability change induced by the perturbation. Based on this formulation, we propose a PCA using potential energy terms, and we designate it as potential energy PCA (PEPCA). The PEPCA provides both general applicability and clear physical meaning. For demonstrating its power, we apply the PEPCA to an alanine dipeptide molecule in vacuum as a minimal model of a nonsingle dominant conformational biomolecule. The first and second principal components clearly characterize two stable states and the transition state between them. Positive and negative components with larger absolute values of the first and second eigenvectors identify the electrostatic interactions, which stabilize or destabilize each stable state and the transition state. Our result therefore indicates that PCA can be applied, by carefully selecting the perturbation functions, not only to identify the molecular conformational fluctuation but also to predict the conformational distribution change by the perturbation beyond the limitation of the previous methods.

Accordance of Online Health Information on Prostate Cancer with the European Association of Urology Guidelines.

PubMed

Bruendl, Johannes; Rothbauer, Clemens; Ludwig, Bernd; Dotzler, Bernhard; Wolff, Christian; Reimann, Sandra; Borgmann, Hendrik; Burger, Maximilian; Breyer, Johannes

2018-01-01

The internet is an emerging source of information for prostate cancer (PCa) patients. Since little is known about the quality of information on PCa provided online, we investigated its accordance to the latest European Association of Urology (EAU) guidelines. A total of 89 German web pages were included for analysis. A quality model classifying the provider of information and its expertise was introduced. Correctness of provided information was systematically compared to the EAU guidelines. Information was provided by medical experts (41%), media (11%), and pharmaceutical companies (6%). Certificates were found in 23% with a significantly higher rate if provided by medical experts (p = 0.003). The minority of web pages showed information in accordance with the EAU guidelines regarding screening (63%), diagnosis (32%), classification (39%), therapy (36%), complications (8%), and follow-up (27%). Web pages by medical experts as well as websites with any kind of certification showed a significantly higher guideline conformity regarding diagnosis (p = 0.027, p = 0.002), therapy (p = 0.010, p = 0.011), follow-up (p = 0.005, p < 0.001), and availability of references (p = 0.017, p = 0.003). The present study reveals that online health information on PCa lacks concordance to current guidelines. Certified websites or websites provided by medical experts showed a significantly higher quality and accordance with guidelines. © 2018 S. Karger AG, Basel.

Exosomes secreted by placental stem cells selectively inhibit growth of aggressive prostate cancer cells.

PubMed

Peak, Taylor C; Praharaj, Prakash P; Panigrahi, Gati K; Doyle, Michael; Su, Yixin; Schlaepfer, Isabel R; Singh, Ravi; Vander Griend, Donald J; Alickson, Julie; Hemal, Ashok; Atala, Anthony; Deep, Gagan

2018-05-23

The current paradigm in the development of new cancer therapies is the ability to target tumor cells while avoiding harm to noncancerous cells. Furthermore, there is a need to develop novel therapeutic options against drug-resistant cancer cells. Herein, we characterized the placental-derived stem cell (PLSC) exosomes (PLSC Exo ) and evaluated their anti-cancer efficacy in prostate cancer (PCa) cell lines. Nanoparticle tracking analyses revealed the size distribution (average size 131.4 ± 0.9 nm) and concentration of exosomes (5.23 × 10 10 ±1.99 × 10 9 per ml) secreted by PLSC. PLSC Exo treatment strongly inhibited the viability of enzalutamide-sensitive and -resistant PCa cell lines (C4-2B, CWR-R1, and LNCaP cells). Interestingly, PLSC Exo treatment had no effect on the viability of a non-neoplastic human prostate cell line (PREC-1). Mass spectrometry (MS) analyses showed that PLSC Exo are loaded with 241 proteins and mainly with saturated fatty acids. Further, Ingenuity Pathway Analysis analyses of proteins loaded in PLSC Exo suggested the role of retinoic acid receptor/liver x receptor pathways in their biological effects. Together, these results suggest the novel selective anti-cancer effects of PLSC Exo against aggressive PCa cells. Copyright © 2018 Elsevier Inc. All rights reserved.

Volatile Compounds Produced by Lactobacillus paracasei During Oat Fermentation.

PubMed

Lee, Sang Mi; Oh, Jieun; Hurh, Byung-Serk; Jeong, Gwi-Hwa; Shin, Young-Keum; Kim, Young-Suk

2016-12-01

This study investigated the profiles of volatile compounds produced by Lactobacillus paracasei during oat fermentation using gas chromatography-mass spectrometry coupled with headspace solid-phase microextraction method. A total of 60 compounds, including acids, alcohols, aldehydes, esters, furan derivatives, hydrocarbons, ketones, sulfur-containing compounds, terpenes, and other compounds, were identified in fermented oat. Lipid oxidation products such as 2-pentylfuran, 1-octen-3-ol, hexanal, and nonanal were found to be the main contributors to oat samples fermented by L. paracasei with the level of 2-pentylfuran being the highest. In addition, the contents of ketones, alcohols, acids, and furan derivatives in the oat samples consistently increased with the fermentation time. On the other hand, the contents of degradation products of amino acids, such as 3-methylbutanal, benzaldehyde, acetophenone, dimethyl sulfide, and dimethyl disulfide, decreased in oat samples during fermentation. Principal component analysis (PCA) was applied to discriminate the fermented oat samples according to different fermentation times. The fermented oats were clearly differentiated on PCA plots. The initial fermentation stage was mainly affected by aldehydes, whereas the later samples of fermented oats were strongly associated with acids, alcohols, furan derivatives, and ketones. The application of PCA to data of the volatile profiles revealed that the oat samples fermented by L. paracasei could be distinguished according to fermentation time. © 2016 Institute of Food Technologists®.

Transcript Levels of Androgen Receptor Variant 7 and Ubiquitin-Conjugating Enzyme 2C in Hormone Sensitive Prostate Cancer and Castration-Resistant Prostate Cancer.

PubMed

Lee, Chan Ho; Ku, Ja Yoon; Ha, Jung Min; Bae, Sun Sik; Lee, Jeong Zoo; Kim, Choung-Soo; Ha, Hong Koo

2017-01-01

This study is designed to identify the androgen receptor variant 7 (AR-V7) status, clinical significance of AR-V7 in hormone sensitive prostate cancer (HSPC). Then, we evaluated AR-V7 and changes of its target gene, ubiquitin-conjugating enzyme E2C (UBE2C) which is an anaphase-promoting complex/cyclosome (APC/C)-specific ubiquitin-conjugating enzyme, in castration-resistant prostate cancer (CRPC) in serial tumor biopsies from patients receiving androgen deprivation therapy. We used RT-PCR and Q-PCR assay to evaluate AR-V7, androgen receptor full length (AR-FL), and UBE2C in tumor biopsies from patients with HSPC and CRPC. We examined associations between mRNA expression of AR-V7 and clinicopathologic factors. Furthermore, to identify other potential genes involved in the development of CRPC, RNA sequencing was conducted, using paired prostate cancer (PCa) tissues obtained immediately prior to treatment and at the time of therapeutic resistance. A total of 13 HSPC patients and three CRPC patients were enrolled. Neither a high Gleason score (score of 8 and 9) nor a high risk of PCa (a high risk of locally advanced PCa according to NCCN guidelines) was correlated with mRNA expression of AR-V7 in HSPC (P = 0.153 and P = 0.215). The mRNA expression of AR-FL, but not AR-V7, was significantly associated with the mRNA expression of UBE2C level in HSPC (P = 0.007). However, increased expression of AR-V7, not AR-FL, paralleled increased expression of UBE2C in the CRPC specimens (P = 0.03). AR-V7 expression status before ADT was likely related to shorter CRPC development in patients treating ADT. The result of the RNA-sequencing analysis using serial samples from the same patient before and after castration demonstrated an increased level of the PI3K regulatory subunit 1 (P = 0.018). Our study revealed the role of UBE2C as a marker of the androgen signaling pathway in PCa. Differential gene expression analysis using serial samples from the same patient before and after castration revealed potential genes and pathways involved in development of CRPC. Further studies are needed to determine whether these genes and pathways are potential therapeutic target for CRPC. Prostate 77:60-71, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Study on the main components interaction from Flos Lonicerae and Fructus Forsythiae and their dissolution in vitro and intestinal absorption in rats.

PubMed

Zhou, Wei; Tan, Xiaobin; Shan, Jinjun; Wang, Shouchuan; Yin, Ailing; Cai, Baochang; Di, Liuqing

2014-01-01

The Flos Lonicerae-Fructus Forsythiae herb couple is the basic components of Chinese herbal preparations (Shuang-Huang-Lian tablet, Yin-Qiao-Jie-Du tablet and Fufang Qin-Lan oral liquid), and its pharmacological effects were significantly higher than that in Flos Lonicerae or Fructus Forsythiae, but the reasons remained unknown. In the present study, pattern recognition analysis (hierarchical cluster analysis (HCA) and principal component analysis (PCA)) combined with UHPLC-ESI/LTQ-Orbitrap MS system were performed to study the chemical constitution difference between co-decoction and mixed decoction in the term of chemistry. Besides, the pharmacokinetics in vivo and intestinal absorption in vitro combined with pattern recognition analysis were used to reveal the discrepancy between herb couple and single herbs in the view of biology. The observation from the chemical view in vitro showed that there was significant difference in quantity between co-decoction and mixed decoction by HCA, and the exposure level of isoforsythoside and 3, 5-dicaffeoylquinic acid in co-decoction, higher than that in mixed decoction, directly resulted in the discrepancy between co-decoction and mixed decoction using both PCA and HCA. The observation from the pharmacokinetics displayed that the exposure level in vivo of neochlorogenic acid, 3, 4-dicaffeoylquinic acid, isoforsythoside and forsythoside A, higher than that in single herbs, was the main factor contributing to the difference by both PCA and HCA, interestingly consistent with the results obtained from Caco-2 cells in vitro, which indicated that it was because of intestinal absorption improvement of neochlorogenic acid, 3, 4-dicaffeoylquinic acid, isoforsythoside and forsythoside A that resulted in a better efficacy of herb couple than that of single herbs from the perspective of biology. The results above illustrated that caffeic acid derivatives in Flos Lonicerae-Fructus Forsythiae herb couple could be considered as chemical markers for quality control of its preparations.

Study on the Main Components Interaction from Flos Lonicerae and Fructus Forsythiae and Their Dissolution In Vitro and Intestinal Absorption in Rats

PubMed Central

Zhou, Wei; Tan, Xiaobin; Shan, Jinjun; Wang, Shouchuan; Yin, Ailing; Cai, Baochang; Di, Liuqing

2014-01-01

The Flos Lonicerae-Fructus Forsythiae herb couple is the basic components of Chinese herbal preparations (Shuang-Huang-Lian tablet, Yin-Qiao-Jie-Du tablet and Fufang Qin-Lan oral liquid), and its pharmacological effects were significantly higher than that in Flos Lonicerae or Fructus Forsythiae, but the reasons remained unknown. In the present study, pattern recognition analysis (hierarchical cluster analysis (HCA) and principal component analysis (PCA)) combined with UHPLC-ESI/LTQ-Orbitrap MS system were performed to study the chemical constitution difference between co-decoction and mixed decoction in the term of chemistry. Besides, the pharmacokinetics in vivo and intestinal absorption in vitro combined with pattern recognition analysis were used to reveal the discrepancy between herb couple and single herbs in the view of biology. The observation from the chemical view in vitro showed that there was significant difference in quantity between co-decoction and mixed decoction by HCA, and the exposure level of isoforsythoside and 3, 5-dicaffeoylquinic acid in co-decoction, higher than that in mixed decoction, directly resulted in the discrepancy between co-decoction and mixed decoction using both PCA and HCA. The observation from the pharmacokinetics displayed that the exposure level in vivo of neochlorogenic acid, 3, 4-dicaffeoylquinic acid, isoforsythoside and forsythoside A, higher than that in single herbs, was the main factor contributing to the difference by both PCA and HCA, interestingly consistent with the results obtained from Caco-2 cells in vitro, which indicated that it was because of intestinal absorption improvement of neochlorogenic acid, 3, 4-dicaffeoylquinic acid, isoforsythoside and forsythoside A that resulted in a better efficacy of herb couple than that of single herbs from the perspective of biology. The results above illustrated that caffeic acid derivatives in Flos Lonicerae-Fructus Forsythiae herb couple could be considered as chemical markers for quality control of its preparations. PMID:25275510

ToF-SIMS analysis of poly(L-lysine)-graft-poly(2-methyl-2-oxazoline) ultrathin adlayers.

PubMed

Pidhatika, Bidhari; Chen, Yin; Coullerez, Geraldine; Al-Bataineh, Sameer; Textor, Marcus

2014-02-01

Understanding of the interfacial chemistry of ultrathin polymeric adlayers is fundamentally important in the context of establishing quantitative design rules for the fabrication of nonfouling surfaces in various applications such as biomaterials and medical devices. In this study, seven poly(L-lysine)-graft-poly(2-methyl-2-oxazoline) (PLL-PMOXA) copolymers with grafting density (number of PMOXA chains per lysine residue) 0.09, 0.14, 0.19, 0.33, 0.43, 0.56, and 0.77, respectively, were synthesized and characterized by means of nuclear magnetic resonance spectroscopy (NMR). The copolymers were then adsorbed on Nb2O5 surfaces. Optical waveguide lightmode spectroscopy method was used to monitor the surface adsorption in situ of these copolymers and provide information on adlayer masses that were then converted into PLL and PMOXA surface densities. To investigate the relationship between copolymer bulk architecture (as shown by NMR data) and surface coverage as well as surface architecture, time-of-flight secondary ion mass spectrometry (ToF-SIMS) analysis was performed. Furthermore, ToF-SIMS method combined with principal component analysis (PCA) was used to verify the protein resistant properties of PLL-PMOXA adlayers, by thorough characterization before and after adlayer exposure to human serum. ToF-SIMS analysis revealed that the chemical composition as well as the architecture of the different PLL-PMOXA adlayers indeed reflects the copolymer bulk composition. ToF-SIMS results also indicated a heterogeneous surface coverage of PLL-PMOXA adlayers with high grafting densities higher than 0.33. In the case of protein resistant surface, PCA results showed clear differences between protein resistant and nonprotein-resistant surfaces. Therefore, ToF-SIMS results combined with PCA confirmed that the PLL-PMOXA adlayer with brush architecture resists protein adsorption. However, low increases of some amino acid signals in ToF-SIMS spectra were detected after the adlayer has been exposed to human serum.

Validation of the German revised version of the program in palliative care education and practice questionnaire (PCEP-GR).

PubMed

Fetz, Katharina; Wenzel-Meyburg, Ursula; Schulz-Quach, Christian

2017-12-28

The evaluation of the effectiveness of undergraduate palliative care education (UPCE) programs is an essential foundation to providing high-quality UPCE programs. Therefore, the implementation of valid evaluation tools is indispensable. Until today, there has been no general consensus regarding concrete outcome parameters and their accurate measurement. The Program in Palliative Care Education and Practice Questionnaire (German Revised Version; PCEP-GR) is a promising assessment tool for UPCE. The aim of the current study was to evaluate the psychometric properties of PCEP-GR and to demonstrate its feasibility for the evaluation of UPCE programs. The practical feasibility of the PCEP-GR and its acceptance in medical students were investigated in a pilot study with 24 undergraduate medical students at Heinrich Heine University Dusseldorf, Germany. Subsequently, the PCEP-GR was surveyed in a representative sample (N = 680) of medical students in order to investigate its psychometric properties. Factorial validity was investigated by means of principal component analysis (PCA). Reliability was examined by means of split-half-reliability analysis and analysis of internal consistency. After taking into consideration the PCA and distribution analysis results, an evaluation instruction for the PCEP-GR was developed. The PCEP-GR proved to be feasible and well-accepted in medical students. PCA revealed a four-factorial solution indicating four PCEP-GR subscales: preparation to provide palliative care, attitudes towards palliative care, self-estimation of competence in communication with dying patients and their relatives and self-estimation of knowledge and skills in palliative care. The PCEP-GR showed good split-half-reliability and acceptable to good internal consistency of subscales. Attitudes towards palliative care slightly missed the criterion of acceptable internal consistency. The evaluation instruction suggests a global PCEP-GR index and four subscales. The PCEP-GR has proven to be a feasible, economic, valid and reliable tool for the assessment of UPCE that comprises self-efficacy expectation and relevant attitudes towards palliative care.

Elevated YKL40 is associated with advanced prostate cancer (PCa) and positively regulates invasion and migration of PCa cells

PubMed Central

Jeet, Varinder; Tevz, Gregor; Lehman, Melanie; Hollier, Brett; Nelson, Colleen

2014-01-01

Chitinase 3-like 1 (CHI3L1 or YKL40) is a secreted glycoprotein highly expressed in tumours from patients with advanced stage cancers, including prostate cancer (PCa). The exact function of YKL40 is poorly understood, but it has been shown to play an important role in promoting tumour angiogenesis and metastasis. The therapeutic value and biological function of YKL40 are unknown in PCa. The objective of this study was to examine the expression and function of YKL40 in PCa. Gene expression analysis demonstrated that YKL40 was highly expressed in metastatic PCa cells when compared with less invasive and normal prostate epithelial cell lines. In addition, the expression was primarily limited to androgen receptor-positive cell lines. Evaluation of YKL40 tissue expression in PCa patients showed a progressive increase in patients with aggressive disease when compared with those with less aggressive cancers and normal controls. Treatment of LNCaP and C4-2B cells with androgens increased YKL40 expression, whereas treatment with an anti-androgen agent decreased the gene expression of YKL40 in androgen-sensitive LNCaP cells. Furthermore, knockdown of YKL40 significantly decreased invasion and migration of PCa cells, whereas overexpression rendered them more invasive and migratory, which was commensurate with an enhancement in the anchorage-independent growth of cells. To our knowledge, this study characterises the role of YKL40 for the first time in PCa. Together, these results suggest that YKL40 plays an important role in PCa progression and thus inhibition of YKL40 may be a potential therapeutic strategy for the treatment of PCa. PMID:24981110

Elevated YKL40 is associated with advanced prostate cancer (PCa) and positively regulates invasion and migration of PCa cells.

PubMed

Jeet, Varinder; Tevz, Gregor; Lehman, Melanie; Hollier, Brett; Nelson, Colleen

2014-10-01

Chitinase 3-like 1 (CHI3L1 or YKL40) is a secreted glycoprotein highly expressed in tumours from patients with advanced stage cancers, including prostate cancer (PCa). The exact function of YKL40 is poorly understood, but it has been shown to play an important role in promoting tumour angiogenesis and metastasis. The therapeutic value and biological function of YKL40 are unknown in PCa. The objective of this study was to examine the expression and function of YKL40 in PCa. Gene expression analysis demonstrated that YKL40 was highly expressed in metastatic PCa cells when compared with less invasive and normal prostate epithelial cell lines. In addition, the expression was primarily limited to androgen receptor-positive cell lines. Evaluation of YKL40 tissue expression in PCa patients showed a progressive increase in patients with aggressive disease when compared with those with less aggressive cancers and normal controls. Treatment of LNCaP and C4-2B cells with androgens increased YKL40 expression, whereas treatment with an anti-androgen agent decreased the gene expression of YKL40 in androgen-sensitive LNCaP cells. Furthermore, knockdown of YKL40 significantly decreased invasion and migration of PCa cells, whereas overexpression rendered them more invasive and migratory, which was commensurate with an enhancement in the anchorage-independent growth of cells. To our knowledge, this study characterises the role of YKL40 for the first time in PCa. Together, these results suggest that YKL40 plays an important role in PCa progression and thus inhibition of YKL40 may be a potential therapeutic strategy for the treatment of PCa. © 2014 The authors.

Cluster analysis of commercial samples of Bauhinia spp. using HPLC-UV/PDA and MCR-ALS/PCA without peak alignment procedure.

PubMed

Ardila, Jorge Armando; Funari, Cristiano Soleo; Andrade, André Marques; Cavalheiro, Alberto José; Carneiro, Renato Lajarim

2015-01-01

Bauhinia forficata Link. is recognised by the Brazilian Health Ministry as a treatment of hypoglycemia and diabetes. Analytical methods are useful to assess the plant identity due the similarities found in plants from Bauhinia spp. HPLC-UV/PDA in combination with chemometric tools is an alternative widely used and suitable for authentication of plant material, however, the shifts of retention times for similar compounds in different samples is a problem. To perform comparisons between the authentic medicinal plant (Bauhinia forficata Link.) and samples commercially available in drugstores claiming to be "Bauhinia spp. to treat diabetes" and to evaluate the performance of multivariate curve resolution - alternating least squares (MCR-ALS) associated to principal component analysis (PCA) when compared to pure PCA. HPLC-UV/PDA data obtained from extracts of leaves were evaluated employing a combination of MCR-ALS and PCA, which allowed the use of the full chromatographic and spectrometric information without the need of peak alignment procedures. The use of MCR-ALS/PCA showed better results than the conventional PCA using only one wavelength. Only two of nine commercial samples presented characteristics similar to the authentic Bauhinia forficata spp., considering the full HPLC-UV/PDA data. The combination of MCR-ALS and PCA is very useful when applied to a group of samples where a general alignment procedure could not be applied due to the different chromatographic profiles. This work also demonstrates the need of more strict control from the health authorities regarding herbal products available on the market. Copyright © 2015 John Wiley & Sons, Ltd.

Reading Achievement in Relation to Phonological Coding and Awareness in Deaf Readers: A Meta-Analysis

ERIC Educational Resources Information Center

Mayberry, Rachel I.; del Giudice, Alex A.; Lieberman, Amy M.

2011-01-01

The relation between reading ability and phonological coding and awareness (PCA) skills in individuals who are severely and profoundly deaf was investigated with a meta-analysis. From an initial set of 230 relevant publications, 57 studies were analyzed that experimentally tested PCA skills in 2,078 deaf participants. Half of the studies found…

Functional neural substrates of posterior cortical atrophy patients.

PubMed

Shames, H; Raz, N; Levin, Netta

2015-07-01

Posterior cortical atrophy (PCA) is a neurodegenerative syndrome in which the most pronounced pathologic involvement is in the occipito-parietal visual regions. Herein, we aimed to better define the cortical reflection of this unique syndrome using a thorough battery of behavioral and functional MRI (fMRI) tests. Eight PCA patients underwent extensive testing to map their visual deficits. Assessments included visual functions associated with lower and higher components of the cortical hierarchy, as well as dorsal- and ventral-related cortical functions. fMRI was performed on five patients to examine the neuronal substrate of their visual functions. The PCA patient cohort exhibited stereopsis, saccadic eye movements and higher dorsal stream-related functional impairments, including simultant perception, image orientation, figure-from-ground segregation, closure and spatial orientation. In accordance with the behavioral findings, fMRI revealed intact activation in the ventral visual regions of face and object perception while more dorsal aspects of perception, including motion and gestalt perception, revealed impaired patterns of activity. In most of the patients, there was a lack of activity in the word form area, which is known to be linked to reading disorders. Finally, there was evidence of reduced cortical representation of the peripheral visual field, corresponding to the behaviorally assessed peripheral visual deficit. The findings are discussed in the context of networks extending from parietal regions, which mediate navigationally related processing, visually guided actions, eye movement control and working memory, suggesting that damage to these networks might explain the wide range of deficits in PCA patients.

Correlating the amount of urea, creatinine, and glucose in urine from patients with diabetes mellitus and hypertension with the risk of developing renal lesions by means of Raman spectroscopy and principal component analysis

NASA Astrophysics Data System (ADS)

Bispo, Jeyse Aliana Martins; de Sousa Vieira, Elzo Everton; Silveira, Landulfo; Fernandes, Adriana Barrinha

2013-08-01

Patients with diabetes mellitus and hypertension (HT) diseases are predisposed to kidney diseases. The objective of this study was to identify potential biomarkers in the urine of diabetic and hypertensive patients through Raman spectroscopy in order to predict the evolution to complications and kidney failure. Urine samples were collected from control subjects (CTR) and patients with diabetes and HT with no complications (lower risk, LR), high degree of complications (higher risk, HR), and doing blood dialysis (DI). Urine samples were stored frozen (-20°C) before spectral analysis. Raman spectra were obtained using a dispersive spectrometer (830-nm, 300-mW power, and 20-s accumulation). Spectra were then submitted to principal component analysis (PCA) followed by discriminant analysis. The first PCA loading vectors revealed spectral features of urea, creatinine, and glucose. It has been found that the amounts of urea and creatinine decreased as disease evoluted from CTR to LR/HR and DI (PC1, p<0.05), and the amount of glucose increased in the urine of LR/HR compared to CTR (PC3, p<0.05). The discriminating model showed better overall classification rate of 70%. These results could lead to diagnostic information of possible complications and a better disease prognosis.

Correlating the amount of urea, creatinine, and glucose in urine from patients with diabetes mellitus and hypertension with the risk of developing renal lesions by means of Raman spectroscopy and principal component analysis.

PubMed

Bispo, Jeyse Aliana Martins; de Sousa Vieira, Elzo Everton; Silveira, Landulfo; Fernandes, Adriana Barrinha

2013-08-01

Patients with diabetes mellitus and hypertension (HT) diseases are predisposed to kidney diseases. The objective of this study was to identify potential biomarkers in the urine of diabetic and hypertensive patients through Raman spectroscopy in order to predict the evolution to complications and kidney failure. Urine samples were collected from control subjects (CTR) and patients with diabetes and HT with no complications (lower risk, LR), high degree of complications (higher risk, HR), and doing blood dialysis (DI). Urine samples were stored frozen (-20°C) before spectral analysis. Raman spectra were obtained using a dispersive spectrometer (830-nm, 300-mW power, and 20-s accumulation). Spectra were then submitted to principal component analysis (PCA) followed by discriminant analysis. The first PCA loading vectors revealed spectral features of urea, creatinine, and glucose. It has been found that the amounts of urea and creatinine decreased as disease evoluted from CTR to LR/HR and DI (PC1, p<0.05), and the amount of glucose increased in the urine of LR/HR compared to CTR (PC3, p<0.05). The discriminating model showed better overall classification rate of 70%. These results could lead to diagnostic information of possible complications and a better disease prognosis.

Source attribution of poly- and perfluoroalkyl substances (PFASs) in surface waters from Rhode Island and the New York Metropolitan Area

PubMed Central

Zhang, Xianming; Lohmann, Rainer; Dassuncao, Clifton; Hu, Xindi C.; Weber, Andrea K.; Vecitis, Chad D.; Sunderland, Elsie M.

2017-01-01

Exposure to poly and perfluoroalkyl substances (PFASs) has been associated with adverse health effects in humans and wildlife. Understanding pollution sources is essential for environmental regulation but source attribution for PFASs has been confounded by limited information on industrial releases and rapid changes in chemical production. Here we use principal component analysis (PCA), hierarchical clustering, and geospatial analysis to understand source contributions to 14 PFASs measured across 37 sites in the Northeastern United States in 2014. PFASs are significantly elevated in urban areas compared to rural sites except for perfluorobutane sulfonate (PFBS), N-methyl perfluorooctanesulfonamidoacetic acid (N-MeFOSAA), perfluoroundecanate (PFUnDA) and perfluorododecanate (PFDoDA). The highest PFAS concentrations across sites were for perfluorooctanate (PFOA, 56 ng L−1) and perfluorohexane sulfonate (PFOS, 43 ng L−1) and PFOS levels are lower than earlier measurements of U.S. surface waters. PCA and cluster analysis indicates three main statistical groupings of PFASs. Geospatial analysis of watersheds reveals the first component/cluster originates from a mixture of contemporary point sources such as airports and textile mills. Atmospheric sources from the waste sector are consistent with the second component, and the metal smelting industry plausibly explains the third component. We find this source-attribution technique is effective for better understanding PFAS sources in urban areas. PMID:28217711

Identification of regional activation by factorization of high-density surface EMG signals: A comparison of Principal Component Analysis and Non-negative Matrix factorization.

PubMed

Gallina, Alessio; Garland, S Jayne; Wakeling, James M

2018-05-22

In this study, we investigated whether principal component analysis (PCA) and non-negative matrix factorization (NMF) perform similarly for the identification of regional activation within the human vastus medialis. EMG signals from 64 locations over the VM were collected from twelve participants while performing a low-force isometric knee extension. The envelope of the EMG signal of each channel was calculated by low-pass filtering (8 Hz) the monopolar EMG signal after rectification. The data matrix was factorized using PCA and NMF, and up to 5 factors were considered for each algorithm. Association between explained variance, spatial weights and temporal scores between the two algorithms were compared using Pearson correlation. For both PCA and NMF, a single factor explained approximately 70% of the variance of the signal, while two and three factors explained just over 85% or 90%. The variance explained by PCA and NMF was highly comparable (R > 0.99). Spatial weights and temporal scores extracted with non-negative reconstruction of PCA and NMF were highly associated (all p < 0.001, mean R > 0.97). Regional VM activation can be identified using high-density surface EMG and factorization algorithms. Regional activation explains up to 30% of the variance of the signal, as identified through both PCA and NMF. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

PubMed Central

Mueller, Daniela; Ferrão, Marco Flôres; Marder, Luciano; da Costa, Adilson Ben; de Cássia de Souza Schneider, Rosana

2013-01-01

The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples. PMID:23539030

Comparison of Palivizumab-Like Antibody Binding to Different Conformations of the RSV F Protein in RSV-Infected Adult Hematopoietic Cell Transplant Recipients.

PubMed

Ye, Xunyan; Iwuchukwu, Obinna P; Avadhanula, Vasanthi; Aideyan, Letisha O; McBride, Trevor J; Ferlic-Stark, Laura L; Patel, Kirtida D; Piedra, Felipe-Andres; Shah, Dimpy P; Chemaly, Roy F; Piedra, Pedro A

2018-03-28

Most respiratory syncytial virus (RSV) vaccine candidates include fusion (F) protein in different conformations. Antigenic site II found in the different F conformations is the target of palivizumab, the only US Food and Drug Administration approved monoclonal antibody (mAb). Serum palivizumab-like antibody (PLA) is a potential serologic correlate of immunity. Our objective was to determine if different conformations of F protein in a palivizumab competitive antibody (PCA) assay affect the PLA concentrations. Four PCA assays were standardized using mAbs. Each contained prefusion, postfusion, or intermediate F forms. PLA concentrations were measured in acute and convalescent sera from 22 RSV/A and 18 RSV/B-infected adult hematopoietic cell transplant (HCT) recipients. PLA concentrations were calculated using a 4-parameter logistic regression model and analyzed for statistical significance. PCA assays revealed significantly greater PLA concentrations in convalescent sera; comparable increases in PLA concentration in RSV/A and RSV/B-infected HCT recipients; and significantly reduced PLA concentrations in HCT recipients who shed RSV ≥14 days. A significant positive correlation was observed between PCA assays and RSV neutralizing antibody titers. F protein conformation does not appear to have a measurable impact on PCA assays for measuring PLA induced by RSV/A or RSV/B infection.

A dual yet opposite growth-regulating function of miR-204 and its target XRN1 in prostate adenocarcinoma cells and neuroendocrine-like prostate cancer cells

PubMed Central

Ding, Miao; Lin, Biaoyang; Li, Tao; Liu, Yuanyuan; Li, Yuhua; Zhou, Xiaoyu; Miao, Maohua; Gu, Jinfa; Pan, Hongjie; Yang, Fen; Li, Tianqi; Liu, Xin Yuan; Li, Runsheng

2015-01-01

Androgen deprivation therapy in prostate cancer (PCa) causes neuroendocrine differentiation (NED) of prostatic adenocarcinomas (PAC) cells, leading to recurrence of PCa. Androgen-responsive genes involved in PCa progression including NED remain largely unknown. Here we demonstrated the importance of androgen receptor (AR)-microRNA-204 (miR-204)-XRN1 axis in PCa cell lines and the rat ventral prostate. Androgens downregulate miR-204, resulting in induction of XRN1 (5′-3′ exoribonuclease 1), which we identified as a miR-204 target. miR-204 acts as a tumor suppressor in two PAC cell lines (LNCaP and 22Rv1) and as an oncomiR in two neuroendocrine-like prostate cancer (NEPC) cell lines (PC-3 and CL1). Importantly, overexpression of miR-204 and knockdown of XRN1 inhibited AR expression in PCa cells. Repression of miR-34a, a known AR-targeting miRNA, contributes AR expression by XRN1. Thus we revealed the AR-miR-204-XRN1-miR-34a positive feedback loop and a dual function of miR-204/XRN1 axis in prostate cancer. PMID:25797256

Statistical techniques applied to aerial radiometric surveys (STAARS): principal components analysis user's manual. [NURE program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koch, C.D.; Pirkle, F.L.; Schmidt, J.S.

1981-01-01

A Principal Components Analysis (PCA) has been written to aid in the interpretation of multivariate aerial radiometric data collected by the US Department of Energy (DOE) under the National Uranium Resource Evaluation (NURE) program. The variations exhibited by these data have been reduced and classified into a number of linear combinations by using the PCA program. The PCA program then generates histograms and outlier maps of the individual variates. Black and white plots can be made on a Calcomp plotter by the application of follow-up programs. All programs referred to in this guide were written for a DEC-10. From thismore » analysis a geologist may begin to interpret the data structure. Insight into geological processes underlying the data may be obtained.« less

King's Health Partners' Prostate Cancer Biobank (KHP PCaBB).

PubMed

Saifuddin, S R; Devlies, W; Santaolalla, A; Cahill, F; George, G; Enting, D; Rudman, S; Cathcart, P; Challacombe, B; Dasgupta, P; Galustian, C; Chandra, A; Chowdhury, S; Gillett, C; Van Hemelrijck, M

2017-11-22

The KHP PCaBB was established in 2013 and recruits donors from the Urology or Oncology Departments at Guy's Hospital in London (UK). Prostate cancer patients may be approached to give their consent for biobanking at any point in their treatment pathway, which allows residual material from their earlier diagnosis to be transferred and used by the Biobank. Currently, patients are specifically asked to donate samples of blood and surplus prostate tissue as well as permitting access to their clinical and pathological data that continues to be added throughout the course of their disease. Between 2013 and 2015, 549 prostate cancer patients gave their consent to the biobank and, the tissue repository collected 489 blood samples, 120 frozen prostate tissue samples and 1064 formalin fixed paraffin embedded diagnostic blocks.Prostate cancer has become a chronic disease in a large proportion of men, with many men receiving multiple subsequent treatments, and their treatment trajectory often spanning over decades. Therefore, this resource aims to provide an ideal research platform to explore potential variations in treatment response as well as disease markers in the different risk categories for prostate cancer.A recent audit of the KHP PCaBB revealed that between 2013 and 2015, 1796 patients were diagnosed with prostate cancer at King's Health Partners (KHP), out of which 549 (30.6%) gave their consent to KHP PCaBB. Comparisons between demographic and clinical characteristics of patients who had consented compared to the total patient population revealed that the KHP PCaBB is demographically representative of the total prostate cancer patient population seen in Guy's and St Thomas' NHS Foundation Trust (GSTT). We observed no differences in distribution of ethnicity (p = 0.507) and socioeconomic status (p = 0.097). Some differences were observed in clinical characteristics, specifically with treatment type - which differed significantly between the patients who had given consent and total patient population.The KHP PCaBB has thereby amassed a rich data and tissue repository that is largely reflective of both the demographic and clinical diversity within the total prostate cancer patient population seen at KHP, making it an ideal platform for prostate cancer research.

Is there any association between National Institute of Health category IV prostatitis and prostate-specific antigen levels in patients with low-risk localized prostate cancer?

PubMed

Doluoglu, Omer Gokhan; Ceylan, Cavit; Kilinc, Fatih; Gazel, Eymen; Resorlu, Berkan; Odabas, Oner

2016-01-01

We investigated the association between National Institute of Health category IV prostatitis and prostate-specific antigen levels in patients with low-risk localized prostate cancer. The data of 440 patients who had undergone prostate biopsies due to high PSA levels and suspicious digital rectal examination findings were reviewed retrospectively. The patients were divided into two groups based on the presence of accompanying NIH IV prostatitis. The exclusion criteria were as follows: Gleason score>6, PSA level>20ng/mL, >2 positive cores, >50% cancerous tissue per biopsy, urinary tract infection, urological interventions at least 1 week previously (cystoscopy, urethral catheterization, or similar procedure), history of prostate biopsy, and history of androgen or 5-alpha reductase use. All patient's age, total PSA and free PSA levels, ratio of free to total PSA, PSA density and prostate volume were recorded. In total, 101 patients were included in the study. Histopathological examination revealed only PCa in 78 (77.2%) patients and PCa+NIH IV prostatitis in 23 (22.7%) patients. The median total PSA level was 7.4 (3.5-20.0) ng/mL in the PCa+NIH IV prostatitis group and 6.5 (0.6-20.0) ng/mL in the PCa group (p=0.67). The PSA level was≤10ng/mL in 60 (76.9%) patients in the PCa group and in 16 (69.6%) patients in the PCa+NIH IV prostatitis group (p=0.32). Our study showed no statistically significant difference in PSA levels between patients with and without NIH IV prostatitis accompanying PCa.

Silibinin inhibits hypoxia-induced HIF-1α-mediated signaling, angiogenesis and lipogenesis in prostate cancer cells: In vitro evidence and in vivo functional imaging and metabolomics

PubMed Central

Deep, Gagan; Kumar, Rahul; Nambiar, Dhanya K.; Jain, Anil K.; Ramteke, Anand M.; Serkova, Natalie J.; Agarwal, Chapla; Agarwal, Rajesh

2017-01-01

Hypoxia is associated with aggressive phenotype and poor prognosis in prostate cancer (PCa) patients suggesting that PCa growth and progression could be controlled via targeting hypoxia-induced signaling and biological effects. Here, we analyzed silibinin (a natural flavonoid) efficacy to target cell growth, angiogenesis and metabolic changes in human PCa, LNCaP and 22Rv1 cells under hypoxic condition. Silibinin treatment inhibited the proliferation, clonogenicity and endothelial cells tube formation by hypoxic (1% O2) PCa cells. Interestingly, hypoxia promoted a lipogenic phenotype in PCa cells via activating acetyl-Co A carboxylase (ACC) and fatty acid synthase (FASN) that was inhibited by silibinin treatment. Importantly, silibinin treatment strongly decreased hypoxia-induced HIF-1α expression in PCa cells together with a strong reduction in hypoxia-induced NADPH oxidase (NOX) activity. HIF-1α overexpression in LNCaP cells significantly increased the lipid accumulation and NOX activity; however, silibinin treatment reduced HIF-1α expression, lipid levels, clonogenicity and NOX activity even in HIF-1α overexpressing LNCaP cells. In vivo, silibinin feeding (200 mg/kg body weight) to male nude mice with 22Rv1 tumors, specifically inhibited tumor vascularity (measured by dynamic contrast-enhanced MRI) resulting in tumor growth inhibition without directly inducing necrosis (as revealed by diffusion-weighted MRI). Silibinin feeding did not significantly affect tumor glucose uptake measured by FDG-PET; however, reduced the lipid synthesis measured by quantitative 1H-NMR metabolomics. IHC analyses of tumor tissues confirmed that silibinin feeding decreased proliferation and angiogenesis as well as reduced HIF-1α, FASN and ACC levels. Together, these findings further support silibinin usefulness against PCa through inhibiting hypoxia-induced signaling. PMID:27533043

Model Reduction via Principe Component Analysis and Markov Chain Monte Carlo (MCMC) Methods

NASA Astrophysics Data System (ADS)

Gong, R.; Chen, J.; Hoversten, M. G.; Luo, J.

2011-12-01

Geophysical and hydrogeological inverse problems often include a large number of unknown parameters, ranging from hundreds to millions, depending on parameterization and problems undertaking. This makes inverse estimation and uncertainty quantification very challenging, especially for those problems in two- or three-dimensional spatial domains. Model reduction technique has the potential of mitigating the curse of dimensionality by reducing total numbers of unknowns while describing the complex subsurface systems adequately. In this study, we explore the use of principal component analysis (PCA) and Markov chain Monte Carlo (MCMC) sampling methods for model reduction through the use of synthetic datasets. We compare the performances of three different but closely related model reduction approaches: (1) PCA methods with geometric sampling (referred to as 'Method 1'), (2) PCA methods with MCMC sampling (referred to as 'Method 2'), and (3) PCA methods with MCMC sampling and inclusion of random effects (referred to as 'Method 3'). We consider a simple convolution model with five unknown parameters as our goal is to understand and visualize the advantages and disadvantages of each method by comparing their inversion results with the corresponding analytical solutions. We generated synthetic data with noise added and invert them under two different situations: (1) the noised data and the covariance matrix for PCA analysis are consistent (referred to as the unbiased case), and (2) the noise data and the covariance matrix are inconsistent (referred to as biased case). In the unbiased case, comparison between the analytical solutions and the inversion results show that all three methods provide good estimates of the true values and Method 1 is computationally more efficient. In terms of uncertainty quantification, Method 1 performs poorly because of relatively small number of samples obtained, Method 2 performs best, and Method 3 overestimates uncertainty due to inclusion of random effects. However, in the biased case, only Method 3 correctly estimates all the unknown parameters, and both Methods 1 and 2 provide wrong values for the biased parameters. The synthetic case study demonstrates that if the covariance matrix for PCA analysis is inconsistent with true models, the PCA methods with geometric or MCMC sampling will provide incorrect estimates.

Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia.

PubMed

Pérez-Rambla, Clara; Puchades-Carrasco, Leonor; García-Flores, María; Rubio-Briones, José; López-Guerrero, José Antonio; Pineda-Lucena, Antonio

2017-01-01

Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results. In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH. Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using 1 H nuclear magnetic resonance ( 1 H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches. The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH. PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.

Regulators of gene expression as biomarkers for prostate cancer

PubMed Central

Willard, Stacey S; Koochekpour, Shahriar

2012-01-01

Recent technological advancements in gene expression analysis have led to the discovery of a promising new group of prostate cancer (PCa) biomarkers that have the potential to influence diagnosis and the prediction of disease severity. The accumulation of deleterious changes in gene expression is a fundamental mechanism of prostate carcinogenesis. Aberrant gene expression can arise from changes in epigenetic regulation or mutation in the genome affecting either key regulatory elements or gene sequences themselves. At the epigenetic level, a myriad of abnormal histone modifications and changes in DNA methylation are found in PCa patients. In addition, many mutations in the genome have been associated with higher PCa risk. Finally, over- or underexpression of key genes involved in cell cycle regulation, apoptosis, cell adhesion and regulation of transcription has been observed. An interesting group of biomarkers are emerging from these studies which may prove more predictive than the standard prostate specific antigen (PSA) serum test. In this review, we discuss recent results in the field of gene expression analysis in PCa including the most promising biomarkers in the areas of epigenetics, genomics and the transcriptome, some of which are currently under investigation as clinical tests for early detection and better prognostic prediction of PCa. PMID:23226612

Breast Shape Analysis With Curvature Estimates and Principal Component Analysis for Cosmetic and Reconstructive Breast Surgery.

PubMed

Catanuto, Giuseppe; Taher, Wafa; Rocco, Nicola; Catalano, Francesca; Allegra, Dario; Milotta, Filippo Luigi Maria; Stanco, Filippo; Gallo, Giovanni; Nava, Maurizio Bruno

2018-03-20

Breast shape is defined utilizing mainly qualitative assessment (full, flat, ptotic) or estimates, such as volume or distances between reference points, that cannot describe it reliably. We will quantitatively describe breast shape with two parameters derived from a statistical methodology denominated principal component analysis (PCA). We created a heterogeneous dataset of breast shapes acquired with a commercial infrared 3-dimensional scanner on which PCA was performed. We plotted on a Cartesian plane the two highest values of PCA for each breast (principal components 1 and 2). Testing of the methodology on a preoperative and postoperative surgical case and test-retest was performed by two operators. The first two principal components derived from PCA are able to characterize the shape of the breast included in the dataset. The test-retest demonstrated that different operators are able to obtain very similar values of PCA. The system is also able to identify major changes in the preoperative and postoperative stages of a two-stage reconstruction. Even minor changes were correctly detected by the system. This methodology can reliably describe the shape of a breast. An expert operator and a newly trained operator can reach similar results in a test/re-testing validation. Once developed and after further validation, this methodology could be employed as a good tool for outcome evaluation, auditing, and benchmarking.

Shift work, night work, and the risk of prostate cancer: A meta-analysis based on 9 cohort studies.

PubMed

Du, Hong-Bing; Bin, Kai-Yun; Liu, Wen-Hong; Yang, Feng-Sheng

2017-11-01

Epidemiology studies suggested that shift work or night work may be linked to prostate cancer (PCa); the relationship, however, remains controversy. PubMed, ScienceDirect, and Embase (Ovid) databases were searched before (started from the building of the databases) February 4, 2017 for eligible cohort studies. We pooled the evidence included by a random- or fixed-effect model, according to the heterogeneity. A predefined subgroup analysis was conducted to see the potential discrepancy between groups. Sensitivity analysis was used to test whether our results were stale. Nine cohort studies were eligible for meta-analysis with 2,570,790 male subjects. Our meta-analysis showed that, under the fixed-effect model, the pooled relevant risk (RR) of PCa was 1.05 (95% confidence interval [CI]: 1.00, 1.11; P = .06; I = 24.00%) for men who had ever engaged in night shift work; and under the random-effect model, the pooled RR was 1.08 (0.99, 1.17; P = .08; I = 24.00%). Subgroup analysis showed the RR of PCa among males in western countries was 1.05 (95% CI: 0.99, 1.11; P = .09; I = 0.00%), while among Asian countries it was 2.45 (95% CI: 1.19, 5.04; P = .02; I = 0.00%); and the RR was 1.04 (95% CI: 0.95, 1.14; P = .40; I = 29.20%) for the high-quality group compared with 1.21 (95% CI: 1.03, 1.41; P = .02; I = 0.00%) for the moderate/low-quality group. Sensitivity analysis showed robust results. Based on the current evidence of cohort studies, we found no obvious association between night shift work and PCa. However, our subgroup analysis suggests that night shift work may increase the risk of PCa in Asian men. Some evidence of a small study effect was observed in this meta-analysis.

A case-control study of lower urinary-tract infections, associated antibiotics and the risk of developing prostate cancer using PCBaSe 3.0.

PubMed

Russell, Beth; Garmo, Hans; Beckmann, Kerri; Stattin, Pär; Adolfsson, Jan; Van Hemelrijck, Mieke

2018-01-01

To investigate the association between lower urinary-tract infections, their associated antibiotics and the subsequent risk of developing PCa. Using data from the Swedish PCBaSe 3.0, we performed a matched case-control study (8762 cases and 43806 controls). Conditional logistic regression analysis was used to assess the association between lower urinary-tract infections, related antibiotics and PCa, whilst adjusting for civil status, education, Charlson Comorbidity Index and time between lower urinary-tract infection and PCa diagnosis. It was found that lower urinary-tract infections did not affect PCa risk, however, having a lower urinary-tract infection or a first antibiotic prescription 6-12 months before PCa were both associated with an increased risk of PCa (OR: 1.50, 95% CI: 1.23-1.82 and 1.96, 1.71-2.25, respectively), as compared to men without lower urinary-tract infections. Compared to men with no prescriptions for antibiotics, men who were prescribed ≥10 antibiotics, were 15% less likely to develop PCa (OR: 0.85, 95% CI: 0.78-0.91). PCa was not found to be associated with diagnosis of a urinary-tract infection or frequency, but was positively associated with short time since diagnoses of lower urinary-tract infection or receiving prescriptions for antibiotics. These observations can likely be explained by detection bias, which highlights the importance of data on the diagnostic work-up when studying potential risk factors for PCa.

Improving the prediction of pathologic outcomes in patients undergoing radical prostatectomy: the value of prostate cancer antigen 3 (PCA3), prostate health index (phi) and sarcosine.

PubMed

Ferro, Matteo; Lucarelli, Giuseppe; Bruzzese, Dario; Perdonà, Sisto; Mazzarella, Claudia; Perruolo, Giuseppe; Marino, Ada; Cosimato, Vincenzo; Giorgio, Emilia; Tagliamonte, Virginia; Bottero, Danilo; De Cobelli, Ottavio; Terracciano, Daniela

2015-02-01

Several efforts have been made to find biomarkers that could help clinicians to preoperatively determine prostate cancer (PCa) pathological characteristics and choose the best therapeutic approach, avoiding over-treatment. On this effort, prostate cancer antigen 3 (PCA3), prostate health index (phi) and sarcosine have been presented as promising tools. We evaluated the ability of these biomarkers to predict the pathologic PCa characteristics within a prospectively collected contemporary cohort of patients who underwent radical prostatectomy (RP) for clinically localized PCa at a single high-volume Institution. The prognostic performance of PCA3, phi and sarcosine were evaluated in 78 patients undergoing RP for biopsy-proven PCa. Receiver operating characteristic (ROC) curve analyses tested the accuracy (area under the curve (AUC)) in predicting PCa pathological characteristics. Decision curve analyses (DCA) were used to assess the clinical benefit of the three biomarkers. We found that PCA3, phi and sarcosine levels were significantly higher in patients with tumor volume (TV)≥0.5 ml, pathologic Gleason sum (GS)≥7 and pT3 disease (all p-values≤0.01). ROC curve analysis showed that phi is an accurate predictor of high-stage (AUC 0.85 [0.77-0.93]), high-grade (AUC 0.83 [0.73-0.93]) and high-volume disease (AUC 0.94 [0.88-0.99]). Sarcosine showed a comparable AUC (0.85 [0.76-0.94]) only for T3 stage prediction, whereas PCA3 score showed lower AUCs, ranging from 0.74 (for GS) to 0.86 (for TV). PCA3, phi and sarcosine are predictors of PCa characteristics at final pathology. Successful clinical translation of these findings would reduce the frequency of surveillance biopsies and may enhance acceptance of active surveillance (AS). Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Prostate extracellular vesicles in patient plasma as a liquid biopsy platform for prostate cancer using nanoscale flow cytometry.

PubMed

Biggs, Colleen N; Siddiqui, Khurram M; Al-Zahrani, Ali A; Pardhan, Siddika; Brett, Sabine I; Guo, Qiu Q; Yang, Jun; Wolf, Philipp; Power, Nicholas E; Durfee, Paul N; MacMillan, Connor D; Townson, Jason L; Brinker, Jeffrey C; Fleshner, Neil E; Izawa, Jonathan I; Chambers, Ann F; Chin, Joseph L; Leong, Hon S

2016-02-23

Extracellular vesicles released by prostate cancer present in seminal fluid, urine, and blood may represent a non-invasive means to identify and prioritize patients with intermediate risk and high risk of prostate cancer. We hypothesize that enumeration of circulating prostate microparticles (PMPs), a type of extracellular vesicle (EV), can identify patients with Gleason Score≥4+4 prostate cancer (PCa) in a manner independent of PSA. Plasmas from healthy volunteers, benign prostatic hyperplasia patients, and PCa patients with various Gleason score patterns were analyzed for PMPs. We used nanoscale flow cytometry to enumerate PMPs which were defined as submicron events (100-1000nm) immunoreactive to anti-PSMA mAb when compared to isotype control labeled samples. Levels of PMPs (counts/µL of plasma) were also compared to CellSearch CTC Subclasses in various PCa metastatic disease subtypes (treatment naïve, castration resistant prostate cancer) and in serially collected plasma sets from patients undergoing radical prostatectomy. PMP levels in plasma as enumerated by nanoscale flow cytometry are effective in distinguishing PCa patients with Gleason Score≥8 disease, a high-risk prognostic factor, from patients with Gleason Score≤7 PCa, which carries an intermediate risk of PCa recurrence. PMP levels were independent of PSA and significantly decreased after surgical resection of the prostate, demonstrating its prognostic potential for clinical follow-up. CTC subclasses did not decrease after prostatectomy and were not effective in distinguishing localized PCa patients from metastatic PCa patients. PMP enumeration was able to identify patients with Gleason Score ≥8 PCa but not patients with Gleason Score 4+3 PCa, but offers greater confidence than CTC counts in identifying patients with metastatic prostate cancer. CTC Subclass analysis was also not effective for post-prostatectomy follow up and for distinguishing metastatic PCa and localized PCa patients. Nanoscale flow cytometry of PMPs presents an emerging biomarker platform for various stages of prostate cancer.

Prostate extracellular vesicles in patient plasma as a liquid biopsy platform for prostate cancer using nanoscale flow cytometry

PubMed Central

Al-Zahrani, Ali A.; Pardhan, Siddika; Brett, Sabine I.; Guo, Qiu Q.; Yang, Jun; Wolf, Philipp; Power, Nicholas E.; Durfee, Paul N.; MacMillan, Connor D.; Townson, Jason L.; Brinker, Jeffrey C.; Fleshner, Neil E.; Izawa, Jonathan I.; Chambers, Ann F.; Chin, Joseph L.; Leong, Hon S.

2016-01-01

Background Extracellular vesicles released by prostate cancer present in seminal fluid, urine, and blood may represent a non-invasive means to identify and prioritize patients with intermediate risk and high risk of prostate cancer. We hypothesize that enumeration of circulating prostate microparticles (PMPs), a type of extracellular vesicle (EV), can identify patients with Gleason Score≥4+4 prostate cancer (PCa) in a manner independent of PSA. Patients and Methods Plasmas from healthy volunteers, benign prostatic hyperplasia patients, and PCa patients with various Gleason score patterns were analyzed for PMPs. We used nanoscale flow cytometry to enumerate PMPs which were defined as submicron events (100-1000nm) immunoreactive to anti-PSMA mAb when compared to isotype control labeled samples. Levels of PMPs (counts/μL of plasma) were also compared to CellSearch CTC Subclasses in various PCa metastatic disease subtypes (treatment naïve, castration resistant prostate cancer) and in serially collected plasma sets from patients undergoing radical prostatectomy. Results PMP levels in plasma as enumerated by nanoscale flow cytometry are effective in distinguishing PCa patients with Gleason Score≥8 disease, a high-risk prognostic factor, from patients with Gleason Score≤7 PCa, which carries an intermediate risk of PCa recurrence. PMP levels were independent of PSA and significantly decreased after surgical resection of the prostate, demonstrating its prognostic potential for clinical follow-up. CTC subclasses did not decrease after prostatectomy and were not effective in distinguishing localized PCa patients from metastatic PCa patients. Conclusions PMP enumeration was able to identify patients with Gleason Score ≥8 PCa but not patients with Gleason Score 4+3 PCa, but offers greater confidence than CTC counts in identifying patients with metastatic prostate cancer. CTC Subclass analysis was also not effective for post-prostatectomy follow up and for distinguishing metastatic PCa and localized PCa patients. Nanoscale flow cytometry of PMPs presents an emerging biomarker platform for various stages of prostate cancer. PMID:26814433

Comparative analysis of Hibiscus sabdariffa (roselle) hot and cold extracts in respect to their potential for α-glucosidase inhibition.

PubMed

Rasheed, Dalia M; Porzel, Andrea; Frolov, Andrei; El Seedi, Hesham R; Wessjohann, Ludger A; Farag, Mohamed A

2018-06-01

Roselle (Hibiscus sabdariffa) is a functional food with potential health benefits, consumed either as hot or cold beverage. To ensure quality control of its various products, accurate measurement of active metabolites is warranted. Herein, we propose a combination of ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) and nuclear magnetic resonance (NMR) analytical platforms for the untargeted characterization of metabolites in two roselle cultivars, Aswan and Sudan-1. The analyses revealed 33 metabolites, including sugars, flavonoids, anthocyanins, phenolic and aliphatic organic acids. Their relative contents in cultivars were assessed via principle component analysis (PCA) and orthogonal projection to latent structures analysis (OPLS). Impact of the different extraction methods (decoction, infusion and maceration) was compared by quantitative 1 H NMR spectroscopy, revealing cold maceration to be optimal for preserving anthocyanins, whereas infusion was more suited for recovering organic acids. The metabolite pattern revealed by the different extraction methods was found in good correlation for their ability to inhibit α-glucosidase enzyme. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Influence Function of Principal Component Analysis by Self-Organizing Rule.

PubMed

Higuchi; Eguchi

1998-07-28

This article is concerned with a neural network approach to principal component analysis (PCA). An algorithm for PCA by the self-organizing rule has been proposed and its robustness observed through the simulation study by Xu and Yuille (1995). In this article, the robustness of the algorithm against outliers is investigated by using the theory of influence function. The influence function of the principal component vector is given in an explicit form. Through this expression, the method is shown to be robust against any directions orthogonal to the principal component vector. In addition, a statistic generated by the self-organizing rule is proposed to assess the influence of data in PCA.

Parallel structure among environmental gradients and three trophic levels in a subarctic estuary

USGS Publications Warehouse

Speckman, Suzann G.; Piatt, John F.; Minte-Vera, C. V.; Parrish, Julia K.

2005-01-01

We assessed spatial and temporal variability in the physical environment of a subarctic estuary, and examined concurrent patterns of chlorophyll α abundance (fluorescence), and zooplankton and forage fish community structure. Surveys were conducted in lower Cook Inlet, Alaska, during late July and early August from 1997 through 1999. Principle components analysis (PCA) revealed that spatial heterogeneity in the physical oceanographic environment of lower Cook Inlet could be modeled as three marine-estuarine gradients characterized by temperature, salinity, bottom depth, and turbidity. The gradients persisted from 1997 through 1999, and PCA explained 68% to 92% of the variance in physical oceanography for each gradient-year combination. Correlations between chlorophyll α abundance and distribution and the PCA axes were weak. Chlorophyll was reduced by turbidity, and low levels occurred in areas with high levels of suspended sediments. Detrended correspondence analysis (DCA) was used to order the sample sites based on species composition and to order the zooplankton and forage fish taxa based on similarities among sample sites for each gradient-year. Correlations between the structure of the physical environment (PCA axis 1) and zooplankton community structure (DCA axis 1) were strong (r = 0.43-0.86) in all years for the three marine-estuarine gradients, suggesting that zooplankton community composition was structured by the physical environment. The physical environment (PCA) and forage fish community structure (DCA) were weakly correlated in all years along Gradient 2, defined by halocline intensity and surface temperature and salinity, even though these physical variables were more important for defining zooplankton habitats. However, the physical environment (PCA) and forage fish community structure (DCA) were strongly correlated along the primary marine-estuarine gradient (#1) in 1997 (r = 0.87) and 1998 (r = 0.82). The correlation was poor (r = 0.32) in 1999, when fish community structure changed markedly in lower Cook Inlet. Capelin (Mallotus villosus), walleye pollock (Theragra chalcogramma), and arrowtooth flounder (Atheresthes stomias) were caught farther north than in previous years. Waters were significantly colder and more saline in 1999, a La Nina year, than in other years of the study. Interannual fluctuations in environmental conditions in lower Cook Inlet did not have substantial effects on zooplankton community structure, although abundance of individual taxa varied significantly. The abundance and distribution of chlorophyll α, zooplankton and forage fish were affected much more by spatial variability in physical oceanography than by interannual variability. Our examination of physical-biological linkages in lower Cook Inlet supports the concept of "bottom-up control," i.e., that variability in the physical environment structures higher trophic-level communities by influencing their distribution and abundance across space.

Parallel structure among environmental gradients and three trophic levels in a subarctic estuary

NASA Astrophysics Data System (ADS)

Speckman, Suzann G.; Piatt, John F.; Minte-Vera, Carolina V.; Parrish, Julia K.

2005-07-01

We assessed spatial and temporal variability in the physical environment of a subarctic estuary, and examined concurrent patterns of chlorophyll α abundance (fluorescence), and zooplankton and forage fish community structure. Surveys were conducted in lower Cook Inlet, Alaska, during late July and early August from 1997 through 1999. Principle components analysis (PCA) revealed that spatial heterogeneity in the physical oceanographic environment of lower Cook Inlet could be modeled as three marine-estuarine gradients characterized by temperature, salinity, bottom depth, and turbidity. The gradients persisted from 1997 through 1999, and PCA explained 68% to 92% of the variance in physical oceanography for each gradient-year combination. Correlations between chlorophyll α abundance and distribution and the PCA axes were weak. Chlorophyll was reduced by turbidity, and low levels occurred in areas with high levels of suspended sediments. Detrended correspondence analysis (DCA) was used to order the sample sites based on species composition and to order the zooplankton and forage fish taxa based on similarities among sample sites for each gradient-year. Correlations between the structure of the physical environment (PCA axis 1) and zooplankton community structure (DCA axis 1) were strong ( r = 0.43-0.86) in all years for the three marine-estuarine gradients, suggesting that zooplankton community composition was structured by the physical environment. The physical environment (PCA) and forage fish community structure (DCA) were weakly correlated in all years along Gradient 2, defined by halocline intensity and surface temperature and salinity, even though these physical variables were more important for defining zooplankton habitats. However, the physical environment (PCA) and forage fish community structure (DCA) were strongly correlated along the primary marine-estuarine gradient (#1) in 1997 ( r = 0.87) and 1998 ( r = 0.82). The correlation was poor ( r = 0.32) in 1999, when fish community structure changed markedly in lower Cook Inlet. Capelin ( Mallotus villosus), walleye pollock ( Theragra chalcogramma), and arrowtooth flounder ( Atheresthes stomias) were caught farther north than in previous years. Waters were significantly colder and more saline in 1999, a La Niña year, than in other years of the study. Interannual fluctuations in environmental conditions in lower Cook Inlet did not have substantial effects on zooplankton community structure, although abundance of individual taxa varied significantly. The abundance and distribution of chlorophyll α, zooplankton and forage fish were affected much more by spatial variability in physical oceanography than by interannual variability. Our examination of physical-biological linkages in lower Cook Inlet supports the concept of “bottom-up control,” i.e., that variability in the physical environment structures higher trophic-level communities by influencing their distribution and abundance across space.

From measurements to metrics: PCA-based indicators of cyber anomaly

NASA Astrophysics Data System (ADS)

Ahmed, Farid; Johnson, Tommy; Tsui, Sonia

2012-06-01

We present a framework of the application of Principal Component Analysis (PCA) to automatically obtain meaningful metrics from intrusion detection measurements. In particular, we report the progress made in applying PCA to analyze the behavioral measurements of malware and provide some preliminary results in selecting dominant attributes from an arbitrary number of malware attributes. The results will be useful in formulating an optimal detection threshold in the principal component space, which can both validate and augment existing malware classifiers.

A novel method for qualitative analysis of edible oil oxidation using an electronic nose.

PubMed

Xu, Lirong; Yu, Xiuzhu; Liu, Lei; Zhang, Rui

2016-07-01

An electronic nose (E-nose) was used for rapid assessment of the degree of oxidation in edible oils. Peroxide and acid values of edible oil samples were analyzed using data obtained by the American Oil Chemists' Society (AOCS) Official Method for reference. Qualitative discrimination between non-oxidized and oxidized oils was conducted using the E-nose technique developed in combination with cluster analysis (CA), principal component analysis (PCA), and linear discriminant analysis (LDA). The results from CA, PCA and LDA indicated that the E-nose technique could be used for differentiation of non-oxidized and oxidized oils. LDA produced slightly better results than CA and PCA. The proposed approach can be used as an alternative to AOCS Official Method as an innovative tool for rapid detection of edible oil oxidation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification, classification, and discrimination of agave syrups from natural sweeteners by infrared spectroscopy and HPAEC-PAD.

PubMed

Mellado-Mojica, Erika; López, Mercedes G

2015-01-15

Agave syrups are gaining popularity as new natural sweeteners. Identification, classification and discrimination by infrared spectroscopy coupled to chemometrics (NIR-MIR-SIMCA-PCA) and HPAEC-PAD of agave syrups from natural sweeteners were achieved. MIR-SIMCA-PCA allowed us to classify the natural sweeteners according to their natural source. Natural syrups exhibited differences in the MIR spectra region 1500-900 cm(-1). The agave syrups displayed strong absorption in the MIR spectra region 1061-1,063 cm(-1), in agreement with their high fructose content. Additionally, MIR-SIMCA-PCA allowed us to differentiate among syrups from different Agave species (Agavetequilana and Agavesalmiana). Thin-layer chromatography and HPAEC-PAD revealed glucose, fructose, and sucrose as the principal carbohydrates in all of the syrups. Oligosaccharide profiles showed that A. tequilana syrups are mainly composed of fructose (>60%) and fructooligosaccharides, while A. salmiana syrups contain more sucrose (28-32%). We conclude that MIR-SIMCA-PCA and HPAEC-PAD can be used to unequivocally identify and classified agave syrups. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Human Prostatic Acid Phosphatase: Structure, Function and Regulation

PubMed Central

Muniyan, Sakthivel; Chaturvedi, Nagendra K.; Dwyer, Jennifer G.; LaGrange, Chad A.; Chaney, William G.; Lin, Ming-Fong

2013-01-01

Human prostatic acid phosphatase (PAcP) is a 100 kDa glycoprotein composed of two subunits. Recent advances demonstrate that cellular PAcP (cPAcP) functions as a protein tyrosine phosphatase by dephosphorylating ErbB-2/Neu/HER-2 at the phosphotyrosine residues in prostate cancer (PCa) cells, which results in reduced tumorigenicity. Further, the interaction of cPAcP and ErbB-2 regulates androgen sensitivity of PCa cells. Knockdown of cPAcP expression allows androgen-sensitive PCa cells to develop the castration-resistant phenotype, where cells proliferate under an androgen-reduced condition. Thus, cPAcP has a significant influence on PCa cell growth. Interestingly, promoter analysis suggests that PAcP expression can be regulated by NF-κB, via a novel binding sequence in an androgen-independent manner. Further understanding of PAcP function and regulation of expression will have a significant impact on understanding PCa progression and therapy. PMID:23698773

[Identification of varieties of textile fibers by using Vis/NIR infrared spectroscopy technique].

PubMed

Wu, Gui-Fang; He, Yong

2010-02-01

The aim of the present paper was to provide new insight into Vis/NIR spectroscopic analysis of textile fibers. In order to achieve rapid identification of the varieties of fibers, the authors selected 5 kinds of fibers of cotton, flax, wool, silk and tencel to do a study with Vis/NIR spectroscopy. Firstly, the spectra of each kind of fiber were scanned by spectrometer, and principal component analysis (PCA) method was used to analyze the characteristics of the pattern of Vis/NIR spectra. Principal component scores scatter plot (PC1 x PC2 x PC3) of fiber indicated the classification effect of five varieties of fibers. The former 6 principal components (PCs) were selected according to the quantity and size of PCs. The PCA classification model was optimized by using the least-squares support vector machines (LS-SVM) method. The authors used the 6 PCs extracted by PCA as the inputs of LS-SVM, and PCA-LS-SVM model was built to achieve varieties validation as well as mathematical model building and optimization analysis. Two hundred samples (40 samples for each variety of fibers) of five varieties of fibers were used for calibration of PCA-LS-SVM model, and the other 50 samples (10 samples for each variety of fibers) were used for validation. The result of validation showed that Vis/NIR spectroscopy technique based on PCA-LS-SVM had a powerful classification capability. It provides a new method for identifying varieties of fibers rapidly and real time, so it has important significance for protecting the rights of consumers, ensuring the quality of textiles, and implementing rationalization production and transaction of textile materials and its production.

TARGETED PRINCIPLE COMPONENT ANALYSIS: A NEW MOTION ARTIFACT CORRECTION APPROACH FOR NEAR-INFRARED SPECTROSCOPY

PubMed Central

YÜCEL, MERYEM A.; SELB, JULIETTE; COOPER, ROBERT J.; BOAS, DAVID A.

2014-01-01

As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease groups, motion artifacts in the NIRS signal due to subject movement is becoming an important challenge. Motion artifacts generally produce signal fluctuations that are larger than physiological NIRS signals, thus it is crucial to correct for them before obtaining an estimate of stimulus evoked hemodynamic responses. There are various methods for correction such as principle component analysis (PCA), wavelet-based filtering and spline interpolation. Here, we introduce a new approach to motion artifact correction, targeted principle component analysis (tPCA), which incorporates a PCA filter only on the segments of data identified as motion artifacts. It is expected that this will overcome the issues of filtering desired signals that plagues standard PCA filtering of entire data sets. We compared the new approach with the most effective motion artifact correction algorithms on a set of data acquired simultaneously with a collodion-fixed probe (low motion artifact content) and a standard Velcro probe (high motion artifact content). Our results show that tPCA gives statistically better results in recovering hemodynamic response function (HRF) as compared to wavelet-based filtering and spline interpolation for the Velcro probe. It results in a significant reduction in mean-squared error (MSE) and significant enhancement in Pearson’s correlation coefficient to the true HRF. The collodion-fixed fiber probe with no motion correction performed better than the Velcro probe corrected for motion artifacts in terms of MSE and Pearson’s correlation coefficient. Thus, if the experimental study permits, the use of a collodion-fixed fiber probe may be desirable. If the use of a collodion-fixed probe is not feasible, then we suggest the use of tPCA in the processing of motion artifact contaminated data. PMID:25360181

Comparison of multi-subject ICA methods for analysis of fMRI data

PubMed Central

Erhardt, Erik Barry; Rachakonda, Srinivas; Bedrick, Edward; Allen, Elena; Adali, Tülay; Calhoun, Vince D.

2010-01-01

Spatial independent component analysis (ICA) applied to functional magnetic resonance imaging (fMRI) data identifies functionally connected networks by estimating spatially independent patterns from their linearly mixed fMRI signals. Several multi-subject ICA approaches estimating subject-specific time courses (TCs) and spatial maps (SMs) have been developed, however there has not yet been a full comparison of the implications of their use. Here, we provide extensive comparisons of four multi-subject ICA approaches in combination with data reduction methods for simulated and fMRI task data. For multi-subject ICA, the data first undergo reduction at the subject and group levels using principal component analysis (PCA). Comparisons of subject-specific, spatial concatenation, and group data mean subject-level reduction strategies using PCA and probabilistic PCA (PPCA) show that computationally intensive PPCA is equivalent to PCA, and that subject-specific and group data mean subject-level PCA are preferred because of well-estimated TCs and SMs. Second, aggregate independent components are estimated using either noise free ICA or probabilistic ICA (PICA). Third, subject-specific SMs and TCs are estimated using back-reconstruction. We compare several direct group ICA (GICA) back-reconstruction approaches (GICA1-GICA3) and an indirect back-reconstruction approach, spatio-temporal regression (STR, or dual regression). Results show the earlier group ICA (GICA1) approximates STR, however STR has contradictory assumptions and may show mixed-component artifacts in estimated SMs. Our evidence-based recommendation is to use GICA3, introduced here, with subject-specific PCA and noise-free ICA, providing the most robust and accurate estimated SMs and TCs in addition to offering an intuitive interpretation. PMID:21162045

Bedside ROP screening and telemedicine interpretation integrated to a neonatal transport system: Economic aspects and return on investment analysis.

PubMed

Kovács, Gábor; Somogyvári, Zsolt; Maka, Erika; Nagyjánosi, László

Peter Cerny Ambulance Service - Premature Eye Rescue Program (PCA-PERP) uses digital retinal imaging (DRI) with remote interpretation in bedside ROP screening, which has advantages over binocular indirect ophthalmoscopy (BIO) in screening of premature newborns. We aimed to demonstrate that PCA-PERP provides good value for the money and to model the cost ramifications of a similar newly launched system. As DRI was demonstrated to have high diagnostic performance, only the costs of bedside DRI-based screening were compared to those of traditional transport and BIO-based screening (cost-minimization analysis). The total costs of investment and maintenance were analyzed with micro-costing method. A ten-year analysis time-horizon and service provider's perspective were applied. From the launch of PCA-PERP up to the end of 2014, 3722 bedside examinations were performed in the PCA covered central region of Hungary. From 2009 to 2014, PCA-PERP saved 92,248km and 3633 staff working hours, with an annual nominal cost-savings ranging from 17,435 to 35,140 Euro. The net present value was 127,847 Euro at the end of 2014, with a payback period of 4.1years and an internal rate of return of 20.8%. Our model presented the NPVs of different scenarios with different initial investments, annual number of transports and average transport distances. PCA-PERP as bedside screening with remote interpretation, when compared to a transport-based screening with BIO, produced better cost-savings from the perspective of the service provider and provided a return on initial investment within five years after the project initiation. Copyright © 2017 Elsevier B.V. All rights reserved.

Principal component analysis of the CT density histogram to generate parametric response maps of COPD

NASA Astrophysics Data System (ADS)

Zha, N.; Capaldi, D. P. I.; Pike, D.; McCormack, D. G.; Cunningham, I. A.; Parraga, G.

2015-03-01

Pulmonary x-ray computed tomography (CT) may be used to characterize emphysema and airways disease in patients with chronic obstructive pulmonary disease (COPD). One analysis approach - parametric response mapping (PMR) utilizes registered inspiratory and expiratory CT image volumes and CT-density-histogram thresholds, but there is no consensus regarding the threshold values used, or their clinical meaning. Principal-component-analysis (PCA) of the CT density histogram can be exploited to quantify emphysema using data-driven CT-density-histogram thresholds. Thus, the objective of this proof-of-concept demonstration was to develop a PRM approach using PCA-derived thresholds in COPD patients and ex-smokers without airflow limitation. Methods: Fifteen COPD ex-smokers and 5 normal ex-smokers were evaluated. Thoracic CT images were also acquired at full inspiration and full expiration and these images were non-rigidly co-registered. PCA was performed for the CT density histograms, from which the components with the highest eigenvalues greater than one were summed. Since the values of the principal component curve correlate directly with the variability in the sample, the maximum and minimum points on the curve were used as threshold values for the PCA-adjusted PRM technique. Results: A significant correlation was determined between conventional and PCA-adjusted PRM with 3He MRI apparent diffusion coefficient (p<0.001), with CT RA950 (p<0.0001), as well as with 3He MRI ventilation defect percent, a measurement of both small airways disease (p=0.049 and p=0.06, respectively) and emphysema (p=0.02). Conclusions: PRM generated using PCA thresholds of the CT density histogram showed significant correlations with CT and 3He MRI measurements of emphysema, but not airways disease.

Brachyury as a potential modulator of androgen receptor activity and a key player in therapy resistance in prostate cancer

PubMed Central

Pinto, Filipe; Pértega-Gomes, Nelma; Vizcaíno, José R.; Andrade, Raquel P.; Cárcano, Flavio M.; Reis, Rui Manuel

2016-01-01

Prostate cancer (PCa) is the most commonly diagnosed neoplasm and the second leading cause of cancer-related deaths in men. Acquisition of resistance to conventional therapy is a major problem for PCa patient management. Several mechanisms have been described to promote therapy resistance in PCa, such as androgen receptor (AR) activation, epithelial-to-mesenchymal transition (EMT), acquisition of stem cell properties and neuroendocrine transdifferentiation (NEtD). Recently, we identified Brachyury as a new biomarker of PCa aggressiveness and poor prognosis. In the present study we aimed to assess the role of Brachyury in PCa therapy resistance. We showed that Brachyury overexpression in prostate cancer cells lines increased resistance to docetaxel and cabazitaxel drugs, whereas Brachyury abrogation induced decrease in therapy resistance. Through ChiP-qPCR assays we further demonstrated that Brachyury is a direct regulator of AR expression as well as of the biomarker AMACR and the mesenchymal markers Snail and Fibronectin. Furthermore, in vitro Brachyury was also able to increase EMT and stem properties. By in silico analysis, clinically human Brachyury-positive PCa samples were associated with biomarkers of PCa aggressiveness and therapy resistance, including PTEN loss, and expression of NEtD markers, ERG and Bcl-2. Taken together, our results indicate that Brachyury contributes to tumor chemotherapy resistance, constituting an attractive target for advanced PCa patients. PMID:27049720

NMR-based metabonomic analysis of the hepatotoxicity induced by combined exposure to PCBs and TCDD in rats

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu Chunfeng; Department of Pharmacology, Basic Medical College, Jiamusi University, Jiamusi 154007; Wang Yimei

2010-11-01

A metabonomic approach using {sup 1}H NMR spectroscopy was adopted to investigate the metabonomic pattern of rat urine after oral administration of environmental endocrine disruptors (EDs) polychlorinated biphenyls (PCBs) and 2,3,7,8-tetrachlorodibenzo- p-dioxin (TCDD) alone or in combination and to explore the possible hepatotoxic mechanisms of combined exposure to PCBs and TCDD. {sup 1}H NMR spectra of urines collected 24 h before and after exposure were analyzed via pattern recognition by using principal component analysis (PCA). Serum biochemistry and liver histopathology indicated significant hepatotoxicity in the rats of the combined group. The PCA scores plots of urinary {sup 1}H NMR datamore » showed that all the treatment groups could be easily distinguished from the control group, so could the PCBs or TCDD group and the combined group. The loadings plots of the PCA revealed remarkable increases in the levels of lactate, glucose, taurine, creatine, and 2-hydroxy-isovaleric acid and reductions in the levels of 2-oxoglutarate, citrate, succinate, hippurate, and trimethylamine-N-oxide in rat urine after exposure. These changes were more striking in the combined group. The changed metabolites may be considered possible biomarker for the hepatotoxicity. The present study demonstrates that combined exposure to PCBs and TCDD induced significant hepatotoxicity in rats, and mitochondrial dysfunction and fatty acid metabolism perturbations might contribute to the hepatotoxicity. There was good conformity between changes in the urine metabonomic pattern and those in serum biochemistry and liver histopathology. These results showed that the NMR-based metabonomic approach may provide a promising technique for the evaluation of the combined toxicity of EDs.« less

Differential distribution of sperm subpopulations and incidence of pleiomorphisms in ejaculates of captive howling monkeys ( Alouatta caraya)

NASA Astrophysics Data System (ADS)

Valle, R. R.; Carvalho, F. M.; Muniz, J. A. P. C.; Leal, C. L. V.; García-Herreros, M.

2013-10-01

The aim of this study was to develop an objective method to determine the incidence of pleiomorphisms and its influence on the distribution of sperm morphometric subpopulations in ejaculates of howling monkeys ( Alouatta caraya) by using a combination of computerized analysis system (ASMA) and principal component analysis (PCA) methods. Ejaculates were collected by electroejaculation methods on a regular basis from five individuals maintained under identical captive environmental, nutritional, and management conditions. Each sperm head was measured for dimensional parameters (Area [ A, (square micrometers)], Perimeter [ P, (micrometers)], Length [ L, (micrometers)], and Width [ W, (micrometers)]) and shape-derived parameters (Ellipticity [( L/ W)], Elongation [( L - W)/( L + W)], and Rugosity [(4л A/ P 2)]). PCA revealed two principal components explaining more than the 96 % of the variance. Clustering methods and discriminant analyzes were performed and seven separate subpopulations were identified. There were differences ( P < 0.001) in the distribution of the seven subpopulations as well as in the incidence of abnormal pleiomorphisms (58.6 %, 49.8 %, 35.1 %, 66.4 %, and 55.1 %, P < 0.05) among the five donors tested. Our results indicated that differences among individuals related to the incidence of pleiomorphisms, and sperm subpopulational structure was not related to the captivity conditions or the sperm collection method, since all individuals were studied under identical conditions. In conclusion, the combination of ASMA and PCA is a useful clinical diagnostic resource for detecting deficiencies in sperm morphology and sperm subpopulations in A. caraya ejaculates that could be used in ex situ conservation programs of threatened species in Alouatta genus or even other endangered neotropical primate species.

Revealing Sources and Distribution Changes of Dissolved Organic Matter (DOM) in Pore Water of Sediment from the Yangtze Estuary

PubMed Central

Wang, Ying; Zhang, Di; Shen, Zhenyao; Feng, Chenghong; Chen, Jing

2013-01-01

Dissolved organic matter (DOM) in sediment pore waters from Yangtze estuary of China based on abundance, UV absorbance, molecular weight distribution and fluorescence were investigated using a combination of various parameters of DOM as well as 3D fluorescence excitation emission matrix spectra (F-EEMS) with the parallel factor and principal component analysis (PARAFAC-PCA). The results indicated that DOM in pore water of Yangtze estuary was very variable which mainly composed of low aromaticity and molecular weight materials. Three humic-like substances (C1, C2, C4) and one protein-like substance (C3) were identified by PARAFAC model. C1, C2 and C4 exhibited same trends and were very similar. The separation of samples on both axes of the PCA showed the difference in DOM properties. C1, C2 and C4 concurrently showed higher positive factor 1 loadings, while C3 showed highly positive factor 2 loadings. The PCA analysis showed a combination contribution of microbial DOM signal and terrestrial DOM signal in the Yangtze estuary. Higher and more variable DOM abundance, aromaticity and molecular weight of surface sediment pore water DOM can be found in the southern nearshore than the other regions primarily due to the influence of frequent and intensive human activities and tributaries inflow in this area. The DOM abundance, aromaticity, molecular weight and fluorescence intensity in core of different depth were relative constant and increased gradually with depth. DOM in core was mainly composed of humic-like material, which was due to higher release of the sedimentary organic material into the porewater during early diagenesis. PMID:24155904

Identifying natural and anthropogenic sources of metals in urban and rural soils using GIS-based data, PCA, and spatial interpolation

PubMed Central

Davis, Harley T.; Aelion, C. Marjorie; McDermott, Suzanne; Lawson, Andrew B.

2009-01-01

Determining sources of neurotoxic metals in rural and urban soils is important for mitigating human exposure. Surface soil from four areas with significant clusters of mental retardation and developmental delay (MR/DD) in children, and one control site were analyzed for nine metals and characterized by soil type, climate, ecological region, land use and industrial facilities using readily-available GIS-based data. Kriging, principal component analysis (PCA) and cluster analysis (CA) were used to identify commonalities of metal distribution. Three MR/DD areas (one rural and two urban) had similar soil types and significantly higher soil metal concentrations. PCA and CA results suggested that Ba, Be and Mn were consistently from natural sources; Pb and Hg from anthropogenic sources; and As, Cr, Cu, and Ni from both sources. Arsenic had low commonality estimates, was highly associated with a third PCA factor, and had a complex distribution, complicating mitigation strategies to minimize concentrations and exposures. PMID:19361902

SESNPCA: Principal Component Analysis Applied to Stripped-Envelope Core-Collapse Supernovae

NASA Astrophysics Data System (ADS)

Williamson, Marc; Bianco, Federica; Modjaz, Maryam

2018-01-01

In the new era of time-domain astronomy, it will become increasingly important to have rigorous, data driven models for classifying transients, including supernovae (SNe). We present the first application of principal component analysis (PCA) to stripped-envelope core-collapse supernovae (SESNe). Previous studies of SNe types Ib, IIb, Ic, and broad-line Ic (Ic-BL) focus only on specific spectral features, while our PCA algorithm uses all of the information contained in each spectrum. We use one of the largest compiled datasets of SESNe, containing over 150 SNe, each with spectra taken at multiple phases. Our work focuses on 49 SNe with spectra taken 15 ± 5 days after maximum V-band light where better distinctions can be made between SNe type Ib and Ic spectra. We find that spectra of SNe type IIb and Ic-BL are separable from the other types in PCA space, indicating that PCA is a promising option for developing a purely data driven model for SESNe classification.

The role of CD147 expression in prostate cancer: a systematic review and meta-analysis.

PubMed

Ye, Yun; Li, Su-Liang; Wang, Yao; Yao, Yang; Wang, Juan; Ma, Yue-Yun; Hao, Xiao-Ke

2016-01-01

There are a number of studies which show that expression of CD147 is increased significantly in prostate cancer (PCa). However, conflicting conclusions have also been reported by other researchers lately. In order to arrive at a clear conclusion, a meta-analysis of eligible studies was conducted. We searched PubMed, MEDLINE, Cochrane Library, and the China National Knowledge Infrastructure databases to identify all the published case-control studies on the relationship between the expression of CD147 and PCa until February 2016. In the end, a total of 930 patients in eight studies were included in the meta-analysis. CD147 expression in the PCa patients increased significantly (odds ratio [OR], 4.65; 95% confidence interval [CI], 3.52-6.14; Z=10.79; P<0.05), but there was obvious heterogeneity between studies (I (2)=92.9%, P<0.05). Subgroup analysis showed that positive expression of CD147 was associated with PCa among the Asian population (OR, 21.01; 95% CI, 12.88-34.28; Z=12.19; P<0.05). Furthermore, it was significantly related to TNM stage (OR, 0.24; 95% CI, 0.17-0.35; Z=7.74; P<0.05), Gleason score (OR, 0.41; 95% CI, 0.31-0.56; Z=5.62; P<0.05), differentiation grade (OR, 0.27; 95% CI, 0.13-0.56; Z=3.47; P<0.05), and pretreatment serum prostate-specific antigen level (OR, 0.07; 95% CI, 0.03-0.16; Z=6.47; P<0.05). Positive expression of CD147 was related to PCa, significant heterogeneity was not found between Asian studies, and the result became more significant. The positive expression of CD147 was significantly related to the clinicopathological characteristics of PCa. This suggests that CD147 plays an essential role in poor prognosis and recurrence prediction.

The role of CD147 expression in prostate cancer: a systematic review and meta-analysis

PubMed Central

Ye, Yun; Li, Su-Liang; Wang, Yao; Yao, Yang; Wang, Juan; Ma, Yue-Yun; Hao, Xiao-Ke

2016-01-01

Background There are a number of studies which show that expression of CD147 is increased significantly in prostate cancer (PCa). However, conflicting conclusions have also been reported by other researchers lately. In order to arrive at a clear conclusion, a meta-analysis of eligible studies was conducted. Materials and methods We searched PubMed, MEDLINE, Cochrane Library, and the China National Knowledge Infrastructure databases to identify all the published case–control studies on the relationship between the expression of CD147 and PCa until February 2016. In the end, a total of 930 patients in eight studies were included in the meta-analysis. Results CD147 expression in the PCa patients increased significantly (odds ratio [OR], 4.65; 95% confidence interval [CI], 3.52–6.14; Z=10.79; P<0.05), but there was obvious heterogeneity between studies (I2=92.9%, P<0.05). Subgroup analysis showed that positive expression of CD147 was associated with PCa among the Asian population (OR, 21.01; 95% CI, 12.88–34.28; Z=12.19; P<0.05). Furthermore, it was significantly related to TNM stage (OR, 0.24; 95% CI, 0.17–0.35; Z=7.74; P<0.05), Gleason score (OR, 0.41; 95% CI, 0.31–0.56; Z=5.62; P<0.05), differentiation grade (OR, 0.27; 95% CI, 0.13–0.56; Z=3.47; P<0.05), and pretreatment serum prostate-specific antigen level (OR, 0.07; 95% CI, 0.03–0.16; Z=6.47; P<0.05). Conclusion Positive expression of CD147 was related to PCa, significant heterogeneity was not found between Asian studies, and the result became more significant. The positive expression of CD147 was significantly related to the clinicopathological characteristics of PCa. This suggests that CD147 plays an essential role in poor prognosis and recurrence prediction. PMID:27536064

An application of principal component analysis to the clavicle and clavicle fixation devices.

PubMed

Daruwalla, Zubin J; Courtis, Patrick; Fitzpatrick, Clare; Fitzpatrick, David; Mullett, Hannan

2010-03-26

Principal component analysis (PCA) enables the building of statistical shape models of bones and joints. This has been used in conjunction with computer assisted surgery in the past. However, PCA of the clavicle has not been performed. Using PCA, we present a novel method that examines the major modes of size and three-dimensional shape variation in male and female clavicles and suggests a method of grouping the clavicle into size and shape categories. Twenty-one high-resolution computerized tomography scans of the clavicle were reconstructed and analyzed using a specifically developed statistical software package. After performing statistical shape analysis, PCA was applied to study the factors that account for anatomical variation. The first principal component representing size accounted for 70.5 percent of anatomical variation. The addition of a further three principal components accounted for almost 87 percent. Using statistical shape analysis, clavicles in males have a greater lateral depth and are longer, wider and thicker than in females. However, the sternal angle in females is larger than in males. PCA confirmed these differences between genders but also noted that men exhibit greater variance and classified clavicles into five morphological groups. This unique approach is the first that standardizes a clavicular orientation. It provides information that is useful to both, the biomedical engineer and clinician. Other applications include implant design with regard to modifying current or designing future clavicle fixation devices. Our findings support the need for further development of clavicle fixation devices and the questioning of whether gender-specific devices are necessary.

Comparative Study of the Effect of Sample Pretreatment and Extraction on the Determination of Flavonoids from Lemon (Citrus limon)

PubMed Central

Ledesma-Escobar, Carlos A.; Priego-Capote, Feliciano; Luque de Castro, María D.

2016-01-01

Background Flavonoids have shown to exert multiple beneficial effects on human health, being also appreciated by both food and pharmaceutical industries. Citrus fruits are a key source of flavonoids, thus promoting studies to obtain them. Characteristics of these studies are the discrepancies among sample pretreatments and among extraction methods, and also the scant number of comparative studies developed so far. Objective Evaluate the effect of both the sample pretreatment and the extraction method on the profile of flavonoids isolated from lemon. Results Extracts from fresh, lyophilized and air-dried samples obtained by shaking extraction (SE), ultrasound-assisted extraction (USAE), microwave-assisted extraction (MAE) and superheated liquid extraction (SHLE) were analyzed by LC–QTOF MS/MS, and 32 flavonoids were tentatively identified using MS/MS information. ANOVA applied to the data from fresh and dehydrated samples and from extraction by the different methods revealed that 26 and 32 flavonoids, respectively, were significant (p≤0.01). The pairwise comparison (Tukey HSD; p≤0.01) showed that lyophilized samples are more different from fresh samples than from air-dried samples; also, principal component analysis (PCA) showed a clear discrimination among sample pretreatment strategies and suggested that such differences are mainly created by the abundance of major flavonoids. On the other hand, pairwise comparison of extraction methods revealed that USAE and MAE provided quite similar extracts, being SHLE extracts different from the other two. In this case, PCA showed a clear discrimination among extraction methods, and their position in the scores plot suggests a lower abundance of flavonoids in the extracts from SHLE. In the two PCA the loadings plots revealed a trend to forming groups according to flavonoid aglycones. Conclusions The present study shows clear discrimination caused by both sample pretreatments and extraction methods. Under the studied conditions, liophilization provides extracts with higher amounts of flavonoids, and USAE is the best method for isolation of these compounds, followed by MAE and SE. On the contrary, the SHLE method was the less favorable to extract flavonoids from citrus owing to degradation. PMID:26807979

A novel in vitro metabolomics approach for neurotoxicity testing, proof of principle for methyl mercury chloride and caffeine.

PubMed

van Vliet, Erwin; Morath, Siegfried; Eskes, Chantra; Linge, Jens; Rappsilber, Juri; Honegger, Paul; Hartung, Thomas; Coecke, Sandra

2008-01-01

There is a need for more efficient methods giving insight into the complex mechanisms of neurotoxicity. Testing strategies including in vitro methods have been proposed to comply with this requirement. With the present study we aimed to develop a novel in vitro approach which mimics in vivo complexity, detects neurotoxicity comprehensively, and provides mechanistic insight. For this purpose we combined rat primary re-aggregating brain cell cultures with a mass spectrometry (MS)-based metabolomics approach. For the proof of principle we treated developing re-aggregating brain cell cultures for 48 h with the neurotoxicant methyl mercury chloride (0.1-100 microM) and the brain stimulant caffeine (1-100 microM) and acquired cellular metabolic profiles. To detect toxicant-induced metabolic alterations the profiles were analysed using commercial software which revealed patterns in the multi-parametric dataset by principal component analyses (PCA), and recognised the most significantly altered metabolites. PCA revealed concentration-dependent cluster formations for methyl mercury chloride (0.1-1 microM), and treatment-dependent cluster formations for caffeine (1-100 microM) at sub-cytotoxic concentrations. Four relevant metabolites responsible for the concentration-dependent alterations following methyl mercury chloride treatment could be identified using MS-MS fragmentation analysis. These were gamma-aminobutyric acid, choline, glutamine, creatine and spermine. Their respective mass ion intensities demonstrated metabolic alterations in line with the literature and suggest that the metabolites could be biomarkers for mechanisms of neurotoxicity or neuroprotection. In addition, we evaluated whether the approach could identify neurotoxic potential by testing eight compounds which have target organ toxicity in the liver, kidney or brain at sub-cytotoxic concentrations. PCA revealed cluster formations largely dependent on target organ toxicity indicating possible potential for the development of a neurotoxicity prediction model. With such results it could be useful to perform a validation study to determine the reliability, relevance and applicability of this approach to neurotoxicity screening. Thus, for the first time we show the benefits and utility of in vitro metabolomics to comprehensively detect neurotoxicity and to discover new biomarkers.

The Pattern of Brain Amyloid Load in Posterior Cortical Atrophy Using 18F-AV45: Is Amyloid the Principal Actor in the Disease?

PubMed Central

Beaufils, Emilie; Ribeiro, Maria Joao; Vierron, Emilie; Vercouillie, Johnny; Dufour-Rainfray, Diane; Cottier, Jean-Philippe; Camus, Vincent; Mondon, Karl; Guilloteau, Denis; Hommet, Caroline

2014-01-01

Background Posterior cortical atrophy (PCA) is characterized by progressive higher-order visuoperceptual dysfunction and praxis declines. This syndrome is related to a number of underlying diseases, including, in most cases, Alzheimer's disease (AD). The aim of this study was to compare the amyloid load with 18F-AV45 positron emission tomography (PET) between PCA and AD subjects. Methods We performed 18F-AV45 PET, cerebrospinal fluid (CSF) biomarker analysis and a neuropsychological assessment in 11 PCA patients and 12 AD patients. Results The global and regional 18F-AV45 uptake was similar in the PCA and AD groups. No significant correlation was observed between global 18F-AV45 uptake and CSF biomarkers or between regional 18F-AV45 uptake and cognitive and affective symptoms. Conclusion This 18F-AV45 PET amyloid imaging study showed no specific regional pattern of cortical 18F-AV45 binding in PCA patients. These results confirm that a distinct clinical phenotype in amnestic AD and PCA is not related to amyloid distribution. PMID:25538727

Study of support vector machine and serum surface-enhanced Raman spectroscopy for noninvasive esophageal cancer detection

NASA Astrophysics Data System (ADS)

Li, Shao-Xin; Zeng, Qiu-Yao; Li, Lin-Fang; Zhang, Yan-Jiao; Wan, Ming-Ming; Liu, Zhi-Ming; Xiong, Hong-Lian; Guo, Zhou-Yi; Liu, Song-Hao

2013-02-01

The ability of combining serum surface-enhanced Raman spectroscopy (SERS) with support vector machine (SVM) for improving classification esophageal cancer patients from normal volunteers is investigated. Two groups of serum SERS spectra based on silver nanoparticles (AgNPs) are obtained: one group from patients with pathologically confirmed esophageal cancer (n=30) and the other group from healthy volunteers (n=31). Principal components analysis (PCA), conventional SVM (C-SVM) and conventional SVM combination with PCA (PCA-SVM) methods are implemented to classify the same spectral dataset. Results show that a diagnostic accuracy of 77.0% is acquired for PCA technique, while diagnostic accuracies of 83.6% and 85.2% are obtained for C-SVM and PCA-SVM methods based on radial basis functions (RBF) models. The results prove that RBF SVM models are superior to PCA algorithm in classification serum SERS spectra. The study demonstrates that serum SERS in combination with SVM technique has great potential to provide an effective and accurate diagnostic schema for noninvasive detection of esophageal cancer.

Computational gene expression profiling under salt stress reveals patterns of co-expression

PubMed Central

Sanchita; Sharma, Ashok

2016-01-01

Plants respond differently to environmental conditions. Among various abiotic stresses, salt stress is a condition where excess salt in soil causes inhibition of plant growth. To understand the response of plants to the stress conditions, identification of the responsible genes is required. Clustering is a data mining technique used to group the genes with similar expression. The genes of a cluster show similar expression and function. We applied clustering algorithms on gene expression data of Solanum tuberosum showing differential expression in Capsicum annuum under salt stress. The clusters, which were common in multiple algorithms were taken further for analysis. Principal component analysis (PCA) further validated the findings of other cluster algorithms by visualizing their clusters in three-dimensional space. Functional annotation results revealed that most of the genes were involved in stress related responses. Our findings suggest that these algorithms may be helpful in the prediction of the function of co-expressed genes. PMID:26981411

Fast Steerable Principal Component Analysis

PubMed Central

Zhao, Zhizhen; Shkolnisky, Yoel; Singer, Amit

2016-01-01

Cryo-electron microscopy nowadays often requires the analysis of hundreds of thousands of 2-D images as large as a few hundred pixels in each direction. Here, we introduce an algorithm that efficiently and accurately performs principal component analysis (PCA) for a large set of 2-D images, and, for each image, the set of its uniform rotations in the plane and their reflections. For a dataset consisting of n images of size L × L pixels, the computational complexity of our algorithm is O(nL3 + L4), while existing algorithms take O(nL4). The new algorithm computes the expansion coefficients of the images in a Fourier–Bessel basis efficiently using the nonuniform fast Fourier transform. We compare the accuracy and efficiency of the new algorithm with traditional PCA and existing algorithms for steerable PCA. PMID:27570801

Raman signatures of ferroic domain walls captured by principal component analysis.

PubMed

Nataf, G F; Barrett, N; Kreisel, J; Guennou, M

2018-01-24

Ferroic domain walls are currently investigated by several state-of-the art techniques in order to get a better understanding of their distinct, functional properties. Here, principal component analysis (PCA) of Raman maps is used to study ferroelectric domain walls (DWs) in LiNbO 3 and ferroelastic DWs in NdGaO 3 . It is shown that PCA allows us to quickly and reliably identify small Raman peak variations at ferroelectric DWs and that the value of a peak shift can be deduced-accurately and without a priori-from a first order Taylor expansion of the spectra. The ability of PCA to separate the contribution of ferroelastic domains and DWs to Raman spectra is emphasized. More generally, our results provide a novel route for the statistical analysis of any property mapped across a DW.

Preliminary identification of unicellular algal genus by using combined confocal resonance Raman spectroscopy with PCA and DPLS analysis

NASA Astrophysics Data System (ADS)

He, Shixuan; Xie, Wanyi; Zhang, Ping; Fang, Shaoxi; Li, Zhe; Tang, Peng; Gao, Xia; Guo, Jinsong; Tlili, Chaker; Wang, Deqiang

2018-02-01

The analysis of algae and dominant alga plays important roles in ecological and environmental fields since it can be used to forecast water bloom and control its potential deleterious effects. Herein, we combine in vivo confocal resonance Raman spectroscopy with multivariate analysis methods to preliminary identify the three algal genera in water blooms at unicellular scale. Statistical analysis of characteristic Raman peaks demonstrates that certain shifts and different normalized intensities, resulting from composition of different carotenoids, exist in Raman spectra of three algal cells. Principal component analysis (PCA) scores and corresponding loading weights show some differences from Raman spectral characteristics which are caused by vibrations of carotenoids in unicellular algae. Then, discriminant partial least squares (DPLS) classification method is used to verify the effectiveness of algal identification with confocal resonance Raman spectroscopy. Our results show that confocal resonance Raman spectroscopy combined with PCA and DPLS could handle the preliminary identification of dominant alga for forecasting and controlling of water blooms.

Rotation of EOFs by the Independent Component Analysis: Towards A Solution of the Mixing Problem in the Decomposition of Geophysical Time Series

NASA Technical Reports Server (NTRS)

Aires, Filipe; Rossow, William B.; Chedin, Alain; Hansen, James E. (Technical Monitor)

2001-01-01

The Independent Component Analysis is a recently developed technique for component extraction. This new method requires the statistical independence of the extracted components, a stronger constraint that uses higher-order statistics, instead of the classical decorrelation, a weaker constraint that uses only second-order statistics. This technique has been used recently for the analysis of geophysical time series with the goal of investigating the causes of variability in observed data (i.e. exploratory approach). We demonstrate with a data simulation experiment that, if initialized with a Principal Component Analysis, the Independent Component Analysis performs a rotation of the classical PCA (or EOF) solution. This rotation uses no localization criterion like other Rotation Techniques (RT), only the global generalization of decorrelation by statistical independence is used. This rotation of the PCA solution seems to be able to solve the tendency of PCA to mix several physical phenomena, even when the signal is just their linear sum.

Classification of alloys using laser induced breakdown spectroscopy with principle component analysis

NASA Astrophysics Data System (ADS)

Syuhada Mangsor, Aneez; Haider Rizvi, Zuhaib; Chaudhary, Kashif; Safwan Aziz, Muhammad

2018-05-01

The study of atomic spectroscopy has contributed to a wide range of scientific applications. In principle, laser induced breakdown spectroscopy (LIBS) method has been used to analyse various types of matter regardless of its physical state, either it is solid, liquid or gas because all elements emit light of characteristic frequencies when it is excited to sufficiently high energy. The aim of this work was to analyse the signature spectrums of each element contained in three different types of samples. Metal alloys of Aluminium, Titanium and Brass with the purities of 75%, 80%, 85%, 90% and 95% were used as the manipulated variable and their LIBS spectra were recorded. The characteristic emission lines of main elements were identified from the spectra as well as its corresponding contents. Principal component analysis (PCA) was carried out using the data from LIBS spectra. Three obvious clusters were observed in 3-dimensional PCA plot which corresponding to the different group of alloys. Findings from this study showed that LIBS technology with the help of principle component analysis could conduct the variety discrimination of alloys demonstrating the capability of LIBS-PCA method in field of spectro-analysis. Thus, LIBS-PCA method is believed to be an effective method for classifying alloys with different percentage of purifications, which was high-cost and time-consuming before.

Principal Component Analysis in the Spectral Analysis of the Dynamic Laser Speckle Patterns

NASA Astrophysics Data System (ADS)

Ribeiro, K. M.; Braga, R. A., Jr.; Horgan, G. W.; Ferreira, D. D.; Safadi, T.

2014-02-01

Dynamic laser speckle is a phenomenon that interprets an optical patterns formed by illuminating a surface under changes with coherent light. Therefore, the dynamic change of the speckle patterns caused by biological material is known as biospeckle. Usually, these patterns of optical interference evolving in time are analyzed by graphical or numerical methods, and the analysis in frequency domain has also been an option, however involving large computational requirements which demands new approaches to filter the images in time. Principal component analysis (PCA) works with the statistical decorrelation of data and it can be used as a data filtering. In this context, the present work evaluated the PCA technique to filter in time the data from the biospeckle images aiming the reduction of time computer consuming and improving the robustness of the filtering. It was used 64 images of biospeckle in time observed in a maize seed. The images were arranged in a data matrix and statistically uncorrelated by PCA technique, and the reconstructed signals were analyzed using the routine graphical and numerical methods to analyze the biospeckle. Results showed the potential of the PCA tool in filtering the dynamic laser speckle data, with the definition of markers of principal components related to the biological phenomena and with the advantage of fast computational processing.

Application of principal component analysis to distinguish patients with schizophrenia from healthy controls based on fractional anisotropy measurements.

PubMed

Caprihan, A; Pearlson, G D; Calhoun, V D

2008-08-15

Principal component analysis (PCA) is often used to reduce the dimension of data before applying more sophisticated data analysis methods such as non-linear classification algorithms or independent component analysis. This practice is based on selecting components corresponding to the largest eigenvalues. If the ultimate goal is separation of data in two groups, then these set of components need not have the most discriminatory power. We measured the distance between two such populations using Mahalanobis distance and chose the eigenvectors to maximize it, a modified PCA method, which we call the discriminant PCA (DPCA). DPCA was applied to diffusion tensor-based fractional anisotropy images to distinguish age-matched schizophrenia subjects from healthy controls. The performance of the proposed method was evaluated by the one-leave-out method. We show that for this fractional anisotropy data set, the classification error with 60 components was close to the minimum error and that the Mahalanobis distance was twice as large with DPCA, than with PCA. Finally, by masking the discriminant function with the white matter tracts of the Johns Hopkins University atlas, we identified left superior longitudinal fasciculus as the tract which gave the least classification error. In addition, with six optimally chosen tracts the classification error was zero.

A case-control study of lower urinary-tract infections, associated antibiotics and the risk of developing prostate cancer using PCBaSe 3.0

PubMed Central

Garmo, Hans; Beckmann, Kerri; Stattin, Pär; Adolfsson, Jan; Van Hemelrijck, Mieke

2018-01-01

Objectives To investigate the association between lower urinary-tract infections, their associated antibiotics and the subsequent risk of developing PCa. Subjects/Patients (or materials) and methods Using data from the Swedish PCBaSe 3.0, we performed a matched case-control study (8762 cases and 43806 controls). Conditional logistic regression analysis was used to assess the association between lower urinary-tract infections, related antibiotics and PCa, whilst adjusting for civil status, education, Charlson Comorbidity Index and time between lower urinary-tract infection and PCa diagnosis. Results It was found that lower urinary-tract infections did not affect PCa risk, however, having a lower urinary-tract infection or a first antibiotic prescription 6–12 months before PCa were both associated with an increased risk of PCa (OR: 1.50, 95% CI: 1.23–1.82 and 1.96, 1.71–2.25, respectively), as compared to men without lower urinary-tract infections. Compared to men with no prescriptions for antibiotics, men who were prescribed ≥10 antibiotics, were 15% less likely to develop PCa (OR: 0.85, 95% CI: 0.78–0.91). Conclusion PCa was not found to be associated with diagnosis of a urinary-tract infection or frequency, but was positively associated with short time since diagnoses of lower urinary-tract infection or receiving prescriptions for antibiotics. These observations can likely be explained by detection bias, which highlights the importance of data on the diagnostic work-up when studying potential risk factors for PCa. PMID:29649268

Ghrelin O-acyltransferase (GOAT) enzyme is overexpressed in prostate cancer, and its levels are associated with patient's metabolic status: Potential value as a non-invasive biomarker.

PubMed

Hormaechea-Agulla, Daniel; Gómez-Gómez, Enrique; Ibáñez-Costa, Alejandro; Carrasco-Valiente, Julia; Rivero-Cortés, Esther; L-López, Fernando; Pedraza-Arevalo, Sergio; Valero-Rosa, José; Sánchez-Sánchez, Rafael; Ortega-Salas, Rosa; Moreno, María M; Gahete, Manuel D; López-Miranda, José; Requena, María J; Castaño, Justo P; Luque, Raúl M

2016-12-01

Ghrelin-O-acyltransferase (GOAT) is the key enzyme regulating ghrelin activity, and has been proposed as a potential therapeutic target for obesity/diabetes and as a biomarker in some endocrine-related cancers. However, GOAT presence and putative role in prostate-cancer (PCa) is largely unknown. Here, we demonstrate, for the first time, that GOAT is overexpressed (mRNA/protein-level) in prostatic tissues (n = 52) and plasma/urine-samples (n = 85) of PCa-patients, compared with matched controls [healthy prostate tissues (n = 12) and plasma/urine-samples from BMI-matched controls (n = 28), respectively]. Interestingly, GOAT levels in PCa-patients correlated with aggressiveness and metabolic conditions (i.e. diabetes). Actually, GOAT expression was regulated by metabolic inputs (i.e. In1-ghrelin, insulin/IGF-I) in cultured normal prostate cells and PCa-cell lines. Importantly, ROC-curve analysis unveiled a valuable diagnostic potential for GOAT to discriminate PCa at the tissue/plasma/urine-level with high sensitivity/specificity, particularly in non-diabetic individuals. Moreover, we discovered that GOAT is secreted by PCa-cells, and that its levels are higher in urine samples from a stimulated post-massage vs. pre-massage prostate-test. In conclusion, plasmatic GOAT levels exhibit high specificity/sensitivity to predict PCa-presence compared with other PCa-biomarkers, especially in non-diabetic individuals, suggesting that GOAT holds potential as a novel non-invasive PCa-biomarker. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The language profile of Posterior Cortical Atrophy

PubMed Central

Crutch, Sebastian J.; Lehmann, Manja; Warren, Jason D.; Rohrer, Jonathan D.

2015-01-01

Background Posterior Cortical Atrophy (PCA) is typically considered to be a visual syndrome, primarily characterised by progressive impairment of visuoperceptual and visuospatial skills. However patients commonly describe early difficulties with word retrieval. This paper details the first systematic analysis of linguistic function in PCA. Characterising and quantifying the aphasia associated with PCA is important for clarifying diagnostic and selection criteria for clinical and research studies. Methods Fifteen patients with PCA, 7 patients with logopenic/phonological aphasia (LPA) and 18 age-matched healthy participants completed a detailed battery of linguistic tests evaluating auditory input processing, repetition and working memory, lexical and grammatical comprehension, single word retrieval and fluency, and spontaneous speech. Results Relative to healthy controls, PCA patients exhibited language impairments across all the domains examined, but with anomia, reduced phonemic fluency and slowed speech rate the most prominent deficits. PCA performance most closely resembled that of LPA patients on tests of auditory input processing, repetition and digit span, but was relatively stronger on tasks of comprehension and spontaneous speech. Conclusions The study demonstrates that in addition to the well-reported degradation of vision, literacy and numeracy, PCA is characterised by a progressive oral language dysfunction with prominent word retrieval difficulties. Overlap in the linguistic profiles of PCA and LPA, which are both most commonly caused by Alzheimer’s disease, further emphasises the notion of a phenotypic continuum between typical and atypical manifestations of the disease. Clarifying the boundaries between AD phenotypes has important implications for diagnosis, clinical trial recruitment and investigations into biological factors driving phenotypic heterogeneity in AD. Rehabilitation strategies to ameliorate the phonological deficit in PCA are required. PMID:23138762

Epigenetics in prostate cancer: biologic and clinical relevance.

PubMed

Jerónimo, Carmen; Bastian, Patrick J; Bjartell, Anders; Carbone, Giuseppina M; Catto, James W F; Clark, Susan J; Henrique, Rui; Nelson, William G; Shariat, Shahrokh F

2011-10-01

Prostate cancer (PCa) is one of the most common human malignancies and arises through genetic and epigenetic alterations. Epigenetic modifications include DNA methylation, histone modifications, and microRNAs (miRNA) and produce heritable changes in gene expression without altering the DNA coding sequence. To review progress in the understanding of PCa epigenetics and to focus upon translational applications of this knowledge. PubMed was searched for publications regarding PCa and DNA methylation, histone modifications, and miRNAs. Reports were selected based on the detail of analysis, mechanistic support of data, novelty, and potential clinical applications. Aberrant DNA methylation (hypo- and hypermethylation) is the best-characterized alteration in PCa and leads to genomic instability and inappropriate gene expression. Global and locus-specific changes in chromatin remodeling are implicated in PCa, with evidence suggesting a causative dysfunction of histone-modifying enzymes. MicroRNA deregulation also contributes to prostate carcinogenesis, including interference with androgen receptor signaling and apoptosis. There are important connections between common genetic alterations (eg, E twenty-six fusion genes) and the altered epigenetic landscape. Owing to the ubiquitous nature of epigenetic alterations, they provide potential biomarkers for PCa detection, diagnosis, assessment of prognosis, and post-treatment surveillance. Altered epigenetic gene regulation is involved in the genesis and progression of PCa. Epigenetic alterations may provide valuable tools for the management of PCa patients and be targeted by pharmacologic compounds that reverse their nature. The potential for epigenetic changes in PCa requires further exploration and validation to enable translation to the clinic. Copyright © 2011 European Association of Urology. Published by Elsevier B.V. All rights reserved.

68Ga-PSMA-11 PET/CT for prostate cancer staging and risk stratification in Chinese patients.

PubMed

Zang, Shiming; Shao, Guoqiang; Cui, Can; Li, Tian-Nv; Huang, Yue; Yao, Xiaochen; Fan, Qiu; Chen, Zejun; Du, Jin; Jia, Ruipeng; Sun, Hongbin; Hua, Zichun; Tang, Jun; Wang, Feng

2017-02-14

We evaluated the clinical utility of 68Ga-PSMA-11 PET/CT for staging and risk stratification of treatment-naïve prostate cancer (PCa) and metastatic castrate-resistant prostate cancer (mCRPC). Twenty-two consecutive patients with treatment-naïve PCa and 18 with mCRPC were enrolled. 68Ga-PSMA-11 PET/CT and magnetic resonance imaging (MRI) were performed for the evaluation of primary prostatic lesions, and bone scans were used for evaluation bone metastasis. Among the 40 patients, 37 (92.5% [22 treatment-naïve PCa, 15 mCRPC]) showed PSMA-avid lesions on 68Ga-PSMA-11 images. Only 3 patients with stable mCRPC after chemotherapy were negative for PSMA. The sensitivity, specificity and accuracy of 68Ga-PSMA-11 imaging were 97.3%, 100.0% and 97.5%, respectively. The maximum standardized uptake (SUVmax) of prostatic lesions was 17.09 ± 11.08 and 13.33 ± 12.31 in treatment-naïve PCa and mCRPC, respectively. 68Ga-PSMA-11 revealed 105 metastatic lymph nodes in 15 patients; the SUVmax was 16.85 ± 9.70 and 7.54 ± 5.20 in treatment-naïve PCa and mCRPC, respectively. 68Ga-PSMA-11 PET/CT also newly detected visceral metastasis in 9 patients (22.5%) and bone metastasis in 29 patients (72.5%). 68Ga-PSMA-11 PET/CT exhibits potential for staging and risk stratification in naïve PCa, as well as improved sensitivity for detection of lymph node and remote metastasis.

Synergistic killing effect of chloroquine and androgen deprivation in LNCaP cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaini, Ramesh R.; Hu, Chien-An A., E-mail: AHu@salud.unm.edu

2012-08-24

Highlights: Black-Right-Pointing-Pointer Chloroquine synergistically killed LNCaP cells during androgen deprivation treatment. Black-Right-Pointing-Pointer Chloroquine inhibited the function of autolysosomes and decreases the cytosolic ATP. Black-Right-Pointing-Pointer Chloroquine induced nuclear and DNA fragmentation in androgen deprived LNCaP. Black-Right-Pointing-Pointer Chloroquine may be an useful adjuvant in hormone ablation therapy in PCa patients. -- Abstract: Modulation of autophagy is a new paradigm in cancer therapeutics. Recently a novel function of chloroquine (CLQ) in inhibiting degradation of autophagic vesicles has been revealed, which raises the question whether CLQ can be used as an adjuvant in targeting autophagic pro-survival mechanism in prostate cancer (PCa). We previously showedmore » that autophagy played a protective role during hormone ablation therapy, in part, by consuming lipid droplets in PCa cells. In addition, blocking autophagy by genetic and pharmacological means in the presence of androgen deprivation caused cell death in PCa cells. To further investigate the importance of autophagy in PCa survival and dissect the role of CLQ in PCa death, we treated hormone responsive LNCaP cells with CLQ in combination with androgen deprivation. We observed that CLQ synergistically killed LNCaP cells during androgen deprivation in a dose- and time-dependent manner. We further confirmed that CLQ inhibited the maturation of autophagic vesicles and decreased the cytosolic ATP. Moreover, CLQ induced nuclear condensation and DNA fragmentation, a hallmark of apoptosis, in androgen deprived LNCaP cells. Taken together, our finding suggests that CLQ may be an useful adjuvant in hormone ablation therapy to improve the therapeutic efficacy.« less

Genetic factors influencing prostate cancer risk in Norwegian men.

PubMed

Chen, Haitao; Ewing, Charles M; Zheng, Sigun; Grindedaal, Eli M; Cooney, Kathleen A; Wiley, Kathleen; Djurovic, Srdjan; Andreassen, Ole A; Axcrona, Karol; Mills, Ian G; Xu, Jianfeng; Maehle, Lovise; Fosså, Sophie D; Isaacs, William B

2018-02-01

Norway has one of the highest rates of death due to prostate cancer (PCa) in the world. To assess the contribution of both common and rare single nucleotide variants (SNPs) to the prostate cancer burden in Norway, we assessed the frequency of the established prostate cancer susceptibility allele, HOXB13 G84E, as well as a series of validated, common PCa risk SNPs in a Norwegian PCa population of 779 patients. The G84E allele was observed in 2.3% of patients compared to 0.7% of control individuals, OR = 3.8, P = 1 × 10-4. While there was a trend toward an earlier age at diagnosis, overall the clinicopathologic features of PCa were not significantly different in G84E carriers and non-carriers. Evaluation of 32 established common risk alleles revealed significant associations of risk alleles at 13 loci, including SNPs at 8q24, and near TET2, SLC22A3, NKX3-1, CASC8, MYC, DAP2IP, MSMB, HNF1B, PPP1R14A, and KLK2/3. When the data for each SNP are combined into a genetic risk score (GRS), Norwegian men within the top decile of GRS have over 5-fold greater risk to be diagnosed with PCa than men with GRS in the lowest decile. These results indicate that risk alleles of HOXB13 and common variant SNPs are important components of inherited PCa risk in the Norwegian population, although these factors appear to contribute little to the malignancy's aggressiveness. © 2017 Wiley Periodicals, Inc.

68Ga-PSMA-11 PET/CT for prostate cancer staging and risk stratification in Chinese patients

PubMed Central

Cui, Can; Li, Tian-Nv; Huang, Yue; Yao, Xiaochen; Fan, Qiu; Chen, Zejun; Du, Jin; Jia, Ruipeng; Sun, Hongbin; Hua, Zichun; Tang, Jun; Wang, Feng

2017-01-01

We evaluated the clinical utility of 68Ga-PSMA-11 PET/CT for staging and risk stratification of treatment-naïve prostate cancer (PCa) and metastatic castrate-resistant prostate cancer (mCRPC). Twenty-two consecutive patients with treatment-naïve PCa and 18 with mCRPC were enrolled. 68Ga-PSMA-11 PET/CT and magnetic resonance imaging (MRI) were performed for the evaluation of primary prostatic lesions, and bone scans were used for evaluation bone metastasis. Among the 40 patients, 37 (92.5% [22 treatment-naïve PCa, 15 mCRPC]) showed PSMA-avid lesions on 68Ga-PSMA-11 images. Only 3 patients with stable mCRPC after chemotherapy were negative for PSMA. The sensitivity, specificity and accuracy of 68Ga-PSMA-11 imaging were 97.3%, 100.0% and 97.5%, respectively. The maximum standardized uptake (SUVmax) of prostatic lesions was 17.09 ± 11.08 and 13.33 ± 12.31 in treatment-naïve PCa and mCRPC, respectively. 68Ga-PSMA-11 revealed 105 metastatic lymph nodes in 15 patients; the SUVmax was 16.85 ± 9.70 and 7.54 ± 5.20 in treatment-naïve PCa and mCRPC, respectively. 68Ga-PSMA-11 PET/CT also newly detected visceral metastasis in 9 patients (22.5%) and bone metastasis in 29 patients (72.5%). 68Ga-PSMA-11 PET/CT exhibits potential for staging and risk stratification in naïve PCa, as well as improved sensitivity for detection of lymph node and remote metastasis. PMID:28103574

Modes of embayed beach dynamics: analysis reveals emergent timescales

NASA Astrophysics Data System (ADS)

Murray, K. T.; Murray, A.; Limber, P. W.; Ells, K. D.

2013-12-01

Embayed beaches, or beaches positioned between rocky headlands, exhibit morphologic changes over many length and time scales. Beach sediment is transported as a result of the day-to-day wave forcing, causing patterns of erosion and accretion. We use the Rocky Coastline Evolution Model (RCEM) to investigate how patterns of shoreline change depend on wave climate (the distribution of wave-approach angles) and beach characteristics. Measuring changes in beach width through time allows us to track the evolution of the shape of the beach and the movement of sand within it. By using Principle Component Analysis (PCA), these changes can be categorized into modes, where the first few modes explain the majority of the variation in the time series. We analyze these modes and how they vary as a function of wave climate and headland/bay aspect ratio. In the purposefully simple RCEM, sediment transport is wave-driven and affected by wave shadowing behind the headlands. The rock elements in our model experiments (including the headlands) are fixed and unerodable so that this analysis can focus purely on sand dynamics between the headlands, without a sand contribution from the headlands or cliffs behind the beach. The wave climate is characterized by dictating the percentage of offshore waves arriving from the left and the percentage of waves arriving from high angles (very oblique to the coastline orientation). A high-angle dominated wave climate tends to amplify coastline perturbations, whereas a lower-angle wave climate is diffusive. By changing the headland/bay aspect ratio and wave climate, we can perform PCA analysis of generalized embayed beaches with differing anatomy and wave climate forcings. Previous work using PCA analysis of embayed beaches focused on specific locations and shorter timescales (<30 years; Short and Trembanis, 2004). By using the RCEM, we can more broadly characterize beach dynamics over longer timescales. The first two PCA modes, which explain a majority of the beach width time series variation (typically >70%), are a 'breathing' mode and a 'rotational' mode. The newly identified breathing mode captures the sand movement from the middle of the beach towards the edges (thickening the beach along the headlands), and the rotational mode describes the movement of sand towards one headland or another, both in response to stochastic fluctuations about the mean wave climate. The two main modes operate independently and on different timescales. In a weakly low-angle dominated wave climate, the breathing mode tends to be the first mode (capturing the most variance), but with greater low-angle dominance (greater morphological diffusivity), the rotational mode tends to be first. The aspect ratio of the bay also affects the order of the modes, because wave shadowing affects sediment transport behind the headlands. Previous work has attributed beach rotation to changes in various climate indices such as the North Atlantic Oscillation (Thomas et al., 2011); however, PCA analysis of the RCEM results suggests that embayed beaches can have characteristic timescales of sand movement that result from internal system dynamics, emerging even within a statistically constant wave climate. These results suggest that morphologic changes in embayed beaches can occur independently of readily identifiable shifts in forcing.

Quorum sensing systems differentially regulate the production of phenazine-1-carboxylic acid in the rhizobacterium Pseudomonas aeruginosa PA1201

PubMed Central

Sun, Shuang; Zhou, Lian; Jin, Kaiming; Jiang, Haixia; He, Ya-Wen

2016-01-01

Pseudomonas aeruginosa strain PA1201 is a newly identified rhizobacterium that produces high levels of the secondary metabolite phenazine-1-carboxylic acid (PCA), the newly registered biopesticide Shenqinmycin. PCA production in liquid batch cultures utilizing a specialized PCA-promoting medium (PPM) typically occurs after the period of most rapid growth, and production is regulated in a quorum sensing (QS)-dependent manner. PA1201 contains two PCA biosynthetic gene clusters phz1 and phz2; both clusters contribute to PCA production, with phz2 making a greater contribution. PA1201 also contains a complete set of genes for four QS systems (LasI/LasR, RhlI/RhlR, PQS/MvfR, and IQS). By using several methods including gene deletion, the construction of promoter-lacZ fusion reporter strains, and RNA-Seq analysis, this study investigated the effects of the four QS systems on bacterial growth, QS signal production, the expression of phz1 and phz2, and PCA production. The possible mechanisms for the strain- and condition-dependent expression of phz1 and phz2 were discussed, and a schematic model was proposed. These findings provide a basis for further genetic engineering of the QS systems to improve PCA production. PMID:27456813

SU-F-R-41: Regularized PCA Can Model Treatment-Related Changes in Head and Neck Patients Using Daily CBCTs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chetvertkov, M; Henry Ford Health System, Detroit, MI; Siddiqui, F

2016-06-15

Purpose: To use daily cone beam CTs (CBCTs) to develop regularized principal component analysis (PCA) models of anatomical changes in head and neck (H&N) patients, to guide replanning decisions in adaptive radiation therapy (ART). Methods: Known deformations were applied to planning CT (pCT) images of 10 H&N patients to model several different systematic anatomical changes. A Pinnacle plugin was used to interpolate systematic changes over 35 fractions, generating a set of 35 synthetic CTs for each patient. Deformation vector fields (DVFs) were acquired between the pCT and synthetic CTs and random fraction-to-fraction changes were superimposed on the DVFs. Standard non-regularizedmore » and regularized patient-specific PCA models were built using the DVFs. The ability of PCA to extract the known deformations was quantified. PCA models were also generated from clinical CBCTs, for which the deformations and DVFs were not known. It was hypothesized that resulting eigenvectors/eigenfunctions with largest eigenvalues represent the major anatomical deformations during the course of treatment. Results: As demonstrated with quantitative results in the supporting document regularized PCA is more successful than standard PCA at capturing systematic changes early in the treatment. Regularized PCA is able to detect smaller systematic changes against the background of random fraction-to-fraction changes. To be successful at guiding ART, regularized PCA should be coupled with models of when anatomical changes occur: early, late or throughout the treatment course. Conclusion: The leading eigenvector/eigenfunction from the both PCA approaches can tentatively be identified as a major systematic change during radiotherapy course when systematic changes are large enough with respect to random fraction-to-fraction changes. In all cases the regularized PCA approach appears to be more reliable at capturing systematic changes, enabling dosimetric consequences to be projected once trends are established early in the treatment course. This work is supported in part by a grant from Varian Medical Systems, Palo Alto, CA.« less

National economic and development indicators and international variation in prostate cancer incidence and mortality: an ecological analysis.

PubMed

Neupane, Subas; Bray, Freddie; Auvinen, Anssi

2017-06-01

Macroeconomic indicators are likely associated with prostate cancer (PCa) incidence and mortality globally, but have rarely been assessed. Data on PCa incidence in 2003-2007 for 49 countries with either nationwide cancer registry or at least two regional registries were obtained from Cancer Incidence in Five Continents Vol X and national PCa mortality for 2012 from GLOBOCAN 2012. We compared PCa incidence and mortality rates with various population-level indicators of health, economy and development in 2000. Poisson and linear regression methods were used to quantify the associations. PCa incidence varied more than 15-fold, being highest in high-income countries. PCa mortality exhibited less variation, with higher rates in many low- and middle-income countries. Healthcare expenditure (rate ratio, RR 1.46, 95 % CI 1.45-1.47) and population growth (RR 1.15, 95 % CI 1.14-1.16), as well as computer and mobile phone density, were associated with a higher PCa incidence, while gross domestic product, GDP (RR 0.94, 95 % CI 0.93-0.95) and overall mortality (RR 0.72, 95 % CI 0.71-0.73) were associated with a low incidence. GDP (RR 0.55, 95 % CI 0.46-0.66) was also associated with a low PCa mortality, while life expectancy (RR 3.93, 95 % CI 3.22-4.79) and healthcare expenditure (RR 1.20, 95 % CI 1.09-1.32) were associated with an elevated mortality. Our results show that healthcare expenditure and, thus, the availability of medical resources are an important contributor to the patterns of international variation in PCa incidence. This suggests that there is an iatrogenic component in the current global epidemic of PCa. On the other hand, higher healthcare expenditure is associated with lower PCa death rates.

Human factors issues and approaches in the spatial layout of a space station control room, including the use of virtual reality as a design analysis tool

NASA Technical Reports Server (NTRS)

Hale, Joseph P., II

1994-01-01

Human Factors Engineering support was provided for the 30% design review of the late Space Station Freedom Payload Control Area (PCA). The PCA was to be the payload operations control room, analogous to the Spacelab Payload Operations Control Center (POCC). This effort began with a systematic collection and refinement of the relevant requirements driving the spatial layout of the consoles and PCA. This information was used as input for specialized human factors analytical tools and techniques in the design and design analysis activities. Design concepts and configuration options were developed and reviewed using sketches, 2-D Computer-Aided Design (CAD) drawings, and immersive Virtual Reality (VR) mockups.

Fast principal component analysis for stacking seismic data

NASA Astrophysics Data System (ADS)

Wu, Juan; Bai, Min

2018-04-01

Stacking seismic data plays an indispensable role in many steps of the seismic data processing and imaging workflow. Optimal stacking of seismic data can help mitigate seismic noise and enhance the principal components to a great extent. Traditional average-based seismic stacking methods cannot obtain optimal performance when the ambient noise is extremely strong. We propose a principal component analysis (PCA) algorithm for stacking seismic data without being sensitive to noise level. Considering the computational bottleneck of the classic PCA algorithm in processing massive seismic data, we propose an efficient PCA algorithm to make the proposed method readily applicable for industrial applications. Two numerically designed examples and one real seismic data are used to demonstrate the performance of the presented method.

Time-oriented hierarchical method for computation of principal components using subspace learning algorithm.

PubMed

Jankovic, Marko; Ogawa, Hidemitsu

2004-10-01

Principal Component Analysis (PCA) and Principal Subspace Analysis (PSA) are classic techniques in statistical data analysis, feature extraction and data compression. Given a set of multivariate measurements, PCA and PSA provide a smaller set of "basis vectors" with less redundancy, and a subspace spanned by them, respectively. Artificial neurons and neural networks have been shown to perform PSA and PCA when gradient ascent (descent) learning rules are used, which is related to the constrained maximization (minimization) of statistical objective functions. Due to their low complexity, such algorithms and their implementation in neural networks are potentially useful in cases of tracking slow changes of correlations in the input data or in updating eigenvectors with new samples. In this paper we propose PCA learning algorithm that is fully homogeneous with respect to neurons. The algorithm is obtained by modification of one of the most famous PSA learning algorithms--Subspace Learning Algorithm (SLA). Modification of the algorithm is based on Time-Oriented Hierarchical Method (TOHM). The method uses two distinct time scales. On a faster time scale PSA algorithm is responsible for the "behavior" of all output neurons. On a slower scale, output neurons will compete for fulfillment of their "own interests". On this scale, basis vectors in the principal subspace are rotated toward the principal eigenvectors. At the end of the paper it will be briefly analyzed how (or why) time-oriented hierarchical method can be used for transformation of any of the existing neural network PSA method, into PCA method.

Spatial Mapping of Pyocyanin in Pseudomonas aeruginosa Bacterial Communities by Surface Enhanced Raman Scattering

PubMed Central

Polisetti, Sneha; Baig, Nameera F.; Morales-Soto, Nydia; Shrout, Joshua D.; Bohn, Paul W.

2017-01-01

Surface Enhanced Raman Spectroscopy (SERS) imaging was used in conjunction with Principal Component Analysis (PCA) for the in situ spatiotemporal mapping of the virulence factor pyocyanin, in communities of the pathogenic bacterium Pseudomonas aeruginosa. The combination of SERS imaging and PCA analysis provides a robust method for characterization of heterogeneous biological systems while circumventing issues associated with interference from sample autofluorescence and low reproducibility of SERS signals. The production of pyocyanin is found to depend both on the growth carbon source and on the specific strain of P. aeruginosa studied. A cystic fibrosis lung isolate strain of P. aeruginosa synthesizes and secretes pyocyanin when grown with glucose and glutamate, while the laboratory strain exhibits detectable production of pyocyanin only when grown with glutamate as the source of carbon. Pyocyanin production in the laboratory strain grown with glucose was below the limit of detection of SERS. In addition, the combination of SERS imaging and PCA can elucidate subtle differences in the molecular composition of biofilms. PCA loading plots from the clinical isolate exhibit features corresponding to vibrational bands of carbohydrates, which represent the mucoid biofilm matrix specific to that isolate, features that are not seen in the PCA loading plots of the laboratory strain. PMID:27354400

Exploring high-affinity binding properties of octamer peptides by principal component analysis of tetramer peptides.

PubMed

Kume, Akiko; Kawai, Shun; Kato, Ryuji; Iwata, Shinmei; Shimizu, Kazunori; Honda, Hiroyuki

2017-02-01

To investigate the binding properties of a peptide sequence, we conducted principal component analysis (PCA) of the physicochemical features of a tetramer peptide library comprised of 512 peptides, and the variables were reduced to two principal components. We selected IL-2 and IgG as model proteins and the binding affinity to these proteins was assayed using the 512 peptides mentioned above. PCA of binding affinity data showed that 16 and 18 variables were suitable for localizing IL-2 and IgG high-affinity binding peptides, respectively, into a restricted region of the PCA plot. We then investigated whether the binding affinity of octamer peptide libraries could be predicted using the identified region in the tetramer PCA. The results show that octamer high-affinity binding peptides were also concentrated in the tetramer high-affinity binding region of both IL-2 and IgG. The average fluorescence intensity of high-affinity binding peptides was 3.3- and 2.1-fold higher than that of low-affinity binding peptides for IL-2 and IgG, respectively. We conclude that PCA may be used to identify octamer peptides with high- or low-affinity binding properties from data from a tetramer peptide library. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Scalable Robust Principal Component Analysis Using Grassmann Averages.

PubMed

Hauberg, Sren; Feragen, Aasa; Enficiaud, Raffi; Black, Michael J

2016-11-01

In large datasets, manual data verification is impossible, and we must expect the number of outliers to increase with data size. While principal component analysis (PCA) can reduce data size, and scalable solutions exist, it is well-known that outliers can arbitrarily corrupt the results. Unfortunately, state-of-the-art approaches for robust PCA are not scalable. We note that in a zero-mean dataset, each observation spans a one-dimensional subspace, giving a point on the Grassmann manifold. We show that the average subspace corresponds to the leading principal component for Gaussian data. We provide a simple algorithm for computing this Grassmann Average ( GA), and show that the subspace estimate is less sensitive to outliers than PCA for general distributions. Because averages can be efficiently computed, we immediately gain scalability. We exploit robust averaging to formulate the Robust Grassmann Average (RGA) as a form of robust PCA. The resulting Trimmed Grassmann Average ( TGA) is appropriate for computer vision because it is robust to pixel outliers. The algorithm has linear computational complexity and minimal memory requirements. We demonstrate TGA for background modeling, video restoration, and shadow removal. We show scalability by performing robust PCA on the entire Star Wars IV movie; a task beyond any current method. Source code is available online.

A measure for objects clustering in principal component analysis biplot: A case study in inter-city buses maintenance cost data

NASA Astrophysics Data System (ADS)

Ginanjar, Irlandia; Pasaribu, Udjianna S.; Indratno, Sapto W.

2017-03-01

This article presents the application of the principal component analysis (PCA) biplot for the needs of data mining. This article aims to simplify and objectify the methods for objects clustering in PCA biplot. The novelty of this paper is to get a measure that can be used to objectify the objects clustering in PCA biplot. Orthonormal eigenvectors, which are the coefficients of a principal component model representing an association between principal components and initial variables. The existence of the association is a valid ground to objects clustering based on principal axes value, thus if m principal axes used in the PCA, then the objects can be classified into 2m clusters. The inter-city buses are clustered based on maintenance costs data by using two principal axes PCA biplot. The buses are clustered into four groups. The first group is the buses with high maintenance costs, especially for lube, and brake canvass. The second group is the buses with high maintenance costs, especially for tire, and filter. The third group is the buses with low maintenance costs, especially for lube, and brake canvass. The fourth group is buses with low maintenance costs, especially for tire, and filter.

Correlated motion of protein subdomains and large-scale conformational flexibility of RecA protein filament

NASA Astrophysics Data System (ADS)

Yu, Garmay; A, Shvetsov; D, Karelov; D, Lebedev; A, Radulescu; M, Petukhov; V, Isaev-Ivanov

2012-02-01

Based on X-ray crystallographic data available at Protein Data Bank, we have built molecular dynamics (MD) models of homologous recombinases RecA from E. coli and D. radiodurans. Functional form of RecA enzyme, which is known to be a long helical filament, was approximated by a trimer, simulated in periodic water box. The MD trajectories were analyzed in terms of large-scale conformational motions that could be detectable by neutron and X-ray scattering techniques. The analysis revealed that large-scale RecA monomer dynamics can be described in terms of relative motions of 7 subdomains. Motion of C-terminal domain was the major contributor to the overall dynamics of protein. Principal component analysis (PCA) of the MD trajectories in the atom coordinate space showed that rotation of C-domain is correlated with the conformational changes in the central domain and N-terminal domain, that forms the monomer-monomer interface. Thus, even though C-terminal domain is relatively far from the interface, its orientation is correlated with large-scale filament conformation. PCA of the trajectories in the main chain dihedral angle coordinate space implicates a co-existence of a several different large-scale conformations of the modeled trimer. In order to clarify the relationship of independent domain orientation with large-scale filament conformation, we have performed analysis of independent domain motion and its implications on the filament geometry.

Characterization of 1,577 Primary Prostate Cancers Reveals Novel Biological and Clinicopathological Insights into Molecular Subtypes

PubMed Central

Tomlins, Scott A.; Alshalalfa, Mohammed; Davicioni, Elai; Erho, Nicholas; Yousefi, Kasra; Zhao, Shuang; Haddad, Zaid; Den, Robert B.; Dicker, Adam P.; Trock, Bruce; DeMarzo, Angelo; Ross, Ashley; Schaeffer, Edward M.; Klein, Eric A.; Magi-Galluzzi, Cristina; Karnes, Jeffery R.; Jenkins, Robert B.; Feng, Felix Y.

2015-01-01

Background Prostate cancer (PCa) molecular subtypes have been defined by essentially mutually exclusive events, including ETS gene fusions (most commonly involving ERG) and SPINK1 over-expression. Clinical assessment may aid in disease stratification, complementing available prognostic tests. Objective To determine the analytical validity and clinicopatholgical associations of microarray-based molecular subtyping. Design, Setting and Participants We analyzed Affymetrix GeneChip expression profiles for 1,577 patients from eight radical prostatectomy (RP) cohorts, including 1,351 cases assessed using the Decipher prognostic assay (performed in a CLIA-certified laboratory). A microarray-based (m-) random forest ERG classification model was trained and validated. Outlier expression analysis was used to predict other mutually exclusive non-ERG ETS gene rearrangements (ETS+) or SPINK1 over-expression (SPINK1+). Outcome Measurements Associations with clinical features and outcomes by multivariable logistic regression analysis and receiver operating curves. Results and Limitations The m-ERG classifier showed 95% accuracy in an independent validation subset (n=155 samples). Across cohorts, 45%, 9%, 8% and 38% of PCa were classified as m-ERG+, m-ETS+, m-SPINK1+, and triple negative (m-ERG−/m-ETS−/m-SPINK1−), respectively. Gene expression profiling supports three underlying molecularly defined groups (m-ERG+, m-ETS+ and m-SPINK1+/triple negative). On multivariable analysis, m-ERG+ tumors were associated with lower preoperative serum PSA and Gleason scores, but enriched for extraprostatic extension (p<0.001). m-ETS+ tumors were associated with seminal vesicle invasion (p=0.01), while m-SPINK1+/triple negative tumors had higher Gleason scores and were more frequent in Black/African American patients (p<0.001). Clinical outcomes were not significantly different between subtypes. Conclusions A clinically available prognostic test (Decipher) can also assess PCa molecular subtypes, obviating the need for additional testing. Clinicopathological differences were found among subtypes based on global expression patterns. PMID:25964175

Metal mixtures in urban and rural populations in the US: The Multi-Ethnic Study of Atherosclerosis and the Strong Heart Study.

PubMed

Pang, Yuanjie; Peng, Roger D; Jones, Miranda R; Francesconi, Kevin A; Goessler, Walter; Howard, Barbara V; Umans, Jason G; Best, Lyle G; Guallar, Eliseo; Post, Wendy S; Kaufman, Joel D; Vaidya, Dhananjay; Navas-Acien, Ana

2016-05-01

Natural and anthropogenic sources of metal exposure differ for urban and rural residents. We searched to identify patterns of metal mixtures which could suggest common environmental sources and/or metabolic pathways of different urinary metals, and compared metal-mixtures in two population-based studies from urban/sub-urban and rural/town areas in the US: the Multi-Ethnic Study of Atherosclerosis (MESA) and the Strong Heart Study (SHS). We studied a random sample of 308 White, Black, Chinese-American, and Hispanic participants in MESA (2000-2002) and 277 American Indian participants in SHS (1998-2003). We used principal component analysis (PCA), cluster analysis (CA), and linear discriminant analysis (LDA) to evaluate nine urinary metals (antimony [Sb], arsenic [As], cadmium [Cd], lead [Pb], molybdenum [Mo], selenium [Se], tungsten [W], uranium [U] and zinc [Zn]). For arsenic, we used the sum of inorganic and methylated species (∑As). All nine urinary metals were higher in SHS compared to MESA participants. PCA and CA revealed the same patterns in SHS, suggesting 4 distinct principal components (PC) or clusters (∑As-U-W, Pb-Sb, Cd-Zn, Mo-Se). In MESA, CA showed 2 large clusters (∑As-Mo-Sb-U-W, Cd-Pb-Se-Zn), while PCA showed 4 PCs (Sb-U-W, Pb-Se-Zn, Cd-Mo, ∑As). LDA indicated that ∑As, U, W, and Zn were the most discriminant variables distinguishing MESA and SHS participants. In SHS, the ∑As-U-W cluster and PC might reflect groundwater contamination in rural areas, and the Cd-Zn cluster and PC could reflect common sources from meat products or metabolic interactions. Among the metals assayed, ∑As, U, W and Zn differed the most between MESA and SHS, possibly reflecting disproportionate exposure from drinking water and perhaps food in rural Native communities compared to urban communities around the US. Copyright © 2016 Elsevier Inc. All rights reserved.